{"components":[{"slug":"context-dev","name":"Context.dev","summary":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","kind":"resource","homepage":"https://www.context.dev","repoUrl":"https://github.com/context-dot-dev/context-typescript-sdk","docsUrl":"https://docs.context.dev","publisher":"","hasMcp":true,"hasApi":true,"costRange":"unknown","composabilityRationale":"","functions":["crawl","search","connect","extract"],"functionProbabilities":[{"functionId":"crawl","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-09-23-context-dev-scrape-anything.md","method":"lexical","observedAt":"2026-09-23T00:00:00.000Z"},{"functionId":"search","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-09-23-context-dev-scrape-anything.md","method":"lexical","observedAt":"2026-09-23T00:00:00.000Z"},{"functionId":"connect","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-09-23-context-dev-scrape-anything.md","method":"lexical","observedAt":"2026-09-23T00:00:00.000Z"},{"functionId":"extract","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-09-23-context-dev-scrape-anything.md","method":"lexical","observedAt":"2026-09-23T00:00:00.000Z"}],"slices":[{"functionId":"crawl","label":"Crawl","note":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","cost":"unknown"},{"functionId":"search","label":"Search","note":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","cost":"unknown"},{"functionId":"connect","label":"Connect","note":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","cost":"unknown"},{"functionId":"extract","label":"Extract","note":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-23-context-dev-scrape-anything.md\nContext.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"text API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"/context-dot-dev/context-typescript-sdk), Python, Ruby, Go, PHP; plus MCP / agent skill / CLI install pages under docs.context.dev.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"s://github.com/context-dot-dev/context-typescript-sdk), Python, Ruby, Go, PHP; plus MCP / agent skill / CLI install pages under docs.context.dev.","at":"2026-09-23T00:00:00.000Z"}],"interfaces":[{"kind":"mcp"},{"kind":"cli"},{"kind":"sdk"},{"kind":"skill"}],"origin":"seed","notes":[],"createdAt":"2026-09-23T00:00:00.000Z","updatedAt":"2026-09-23T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_context-dev","claims":{"name":"Context.dev","summary":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","kind":"resource","publisher":"","homepage":"https://www.context.dev","repoUrl":"https://github.com/context-dot-dev/context-typescript-sdk","docsUrl":"https://docs.context.dev","costRange":"unknown","functions":["crawl","search","connect","extract"],"slices":[{"functionId":"crawl","label":"Crawl","note":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","cost":"unknown"},{"functionId":"search","label":"Search","note":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","cost":"unknown"},{"functionId":"connect","label":"Connect","note":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","cost":"unknown"},{"functionId":"extract","label":"Extract","note":"Context.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","cost":"unknown"}],"interfaces":[{"kind":"mcp"},{"kind":"cli"},{"kind":"sdk"},{"kind":"skill"}],"composabilityRationale":""},"relations":[{"from":"context-dev","to":"soar","kind":"fills-same-slot-as","note":"Shared functions connect, search. Can fill the same function slot."},{"from":"context-dev","to":"gosearch-for-slack-agentic-enterprise-search-custom-ai-agents-and-workflow-au","kind":"fills-same-slot-as","note":"Shared functions connect, search. Can fill the same function slot."},{"from":"context-dev","to":"onyx","kind":"fills-same-slot-as","note":"Shared functions connect, search. Can fill the same function slot."}],"signals":[{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-09-23T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":14,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-23-context-dev-scrape-anything.md\nContext.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"text API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"/context-dot-dev/context-typescript-sdk), Python, Ruby, Go, PHP; plus MCP / agent skill / CLI install pages under docs.context.dev.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"s://github.com/context-dot-dev/context-typescript-sdk), Python, Ruby, Go, PHP; plus MCP / agent skill / CLI install pages under docs.context.dev.","at":"2026-09-23T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.6666666666666666,"contribution":0.06666666666666667,"why":"An MCP surface is declared. An API is declared. Cost is unknown. 2 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.3095666486376143,"contribution":0.043339330809266004,"why":"5 sources cover 1 evidence types. The latest dated evidence is 2026-09-23. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-23-context-dev-scrape-anything.md\nContext.dev (also @getcontextdev; YC S26 per founder/company bios) markets itself as a unified web-context API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"text API for software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"/context-dot-dev/context-typescript-sdk), Python, Ruby, Go, PHP; plus MCP / agent skill / CLI install pages under docs.context.dev.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r software and agents: scrape, crawl, search, brand/people enrichment, monitors, MCP, and SDKs — one API key.","at":"2026-09-23T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"s://github.com/context-dot-dev/context-typescript-sdk), Python, Ruby, Go, PHP; plus MCP / agent skill / CLI install pages under docs.context.dev.","at":"2026-09-23T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":14},{"slug":"box","name":"Box","summary":"Box is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","kind":"resource","homepage":"https://box.ascii.dev/","docsUrl":"https://docs.ascii.dev/box/quickstart","publisher":"","hasMcp":false,"hasApi":true,"costRange":"unknown","composabilityRationale":"","functions":["code","stream"],"functionProbabilities":[{"functionId":"code","value":0.92,"source":"06 Knowledge Library/Resources/coding/2026-08-19-ascii-dev-box.md","method":"lexical","observedAt":"2026-08-19T00:00:00.000Z"},{"functionId":"stream","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-08-19-ascii-dev-box.md","method":"lexical","observedAt":"2026-08-19T00:00:00.000Z"}],"slices":[{"functionId":"code","label":"Code","note":"Box is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","cost":"unknown"},{"functionId":"stream","label":"Stream","note":"Box is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-19-ascii-dev-box.md\nBox is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"}],"interfaces":[{"kind":"cli"},{"kind":"http"}],"origin":"seed","notes":[],"createdAt":"2026-08-19T00:00:00.000Z","updatedAt":"2026-08-19T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_box","claims":{"name":"Box","summary":"Box is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","kind":"resource","publisher":"","homepage":"https://box.ascii.dev/","docsUrl":"https://docs.ascii.dev/box/quickstart","costRange":"unknown","functions":["code","stream"],"slices":[{"functionId":"code","label":"Code","note":"Box is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","cost":"unknown"},{"functionId":"stream","label":"Stream","note":"Box is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","cost":"unknown"}],"interfaces":[{"kind":"cli"},{"kind":"http"}],"composabilityRationale":""},"relations":[{"from":"box","to":"ditto","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."},{"from":"box","to":"opendisk","kind":"alternative-to","note":"Shared functions stream. Same kind and overlapping capability."},{"from":"box","to":"emulators-dev","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."},{"from":"box","to":"firecrawl-pdf-inspector","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."},{"from":"box","to":"best-code-execution-sandbox-for-ai-agents-in-2026","kind":"fills-same-slot-as","note":"Shared functions code, stream. Can fill the same function slot."}],"signals":[{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-08-19T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":10,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-19-ascii-dev-box.md\nBox is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.3333333333333333,"contribution":0.03333333333333333,"why":"No MCP surface is declared. An API is declared. Cost is unknown. 1 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.26214289265639185,"contribution":0.036700004971894865,"why":"3 sources cover 1 evidence types. The latest dated evidence is 2026-08-19. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-19-ascii-dev-box.md\nBox is a managed sandbox product from Ascii (legal entity Dedale AI, Corp.). It sells persistent Linux VMs for coding agents and agent platforms: SSH, Docker inside the VM, a dedicated IPv4 per machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"r machine, snapshot/stop/resume, fork-from-snapshot, optional 60fps desktop stream, and a CLI/API/box prompt path for Claude Code or Codex.","at":"2026-08-19T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":10},{"slug":"ditto","name":"Ditto","summary":"Ditto is an open-source deterministic website cloner from ion.design. Point it at a public URL and it returns a cloned implementation as componentized Next.js or Vite code (Tailwind styling), with marketing copy citing ~5 minutes end-to-end.","kind":"resource","homepage":"https://www.ditto.site/","publisher":"","hasMcp":true,"hasApi":true,"costRange":"unknown","composabilityRationale":"","functions":["code"],"functionProbabilities":[{"functionId":"code","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-07-07-ion-design-ditto-site.md","method":"lexical","observedAt":"2026-07-07T00:00:00.000Z"}],"slices":[{"functionId":"code","label":"Code","note":"Ditto is an open-source deterministic website cloner from ion.design. Point it at a public URL and it returns a cloned implementation as componentized Next.js or Vite code (Tailwind styling), with marketing copy citing ~5 minutes end-to-end.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-07-07-ion-design-ditto-site.md\nDitto is an open-source deterministic website cloner from ion.design. Point it at a public URL and it returns a cloned implementation as componentized Next.js or Vite code (Tailwind styling), with marketing copy citing ~5 minutes end-to-end.","at":"2026-07-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"MCP server — https://api.ditto.site/mcp with API key for Claude/Cursor/agent loops.","at":"2026-07-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Hosted REST API — POST https://api.ditto.site/v1/clones, poll job/events, download project (framework: ne","at":"2026-07-07T00:00:00.000Z"}],"interfaces":[{"kind":"mcp"},{"kind":"http"}],"origin":"seed","notes":[],"createdAt":"2026-07-07T00:00:00.000Z","updatedAt":"2026-07-07T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_ditto","claims":{"name":"Ditto","summary":"Ditto is an open-source deterministic website cloner from ion.design. Point it at a public URL and it returns a cloned implementation as componentized Next.js or Vite code (Tailwind styling), with marketing copy citing ~5 minutes end-to-end.","kind":"resource","publisher":"","homepage":"https://www.ditto.site/","costRange":"unknown","functions":["code"],"slices":[{"functionId":"code","label":"Code","note":"Ditto is an open-source deterministic website cloner from ion.design. Point it at a public URL and it returns a cloned implementation as componentized Next.js or Vite code (Tailwind styling), with marketing copy citing ~5 minutes end-to-end.","cost":"unknown"}],"interfaces":[{"kind":"mcp"},{"kind":"http"}],"composabilityRationale":""},"relations":[{"from":"ditto","to":"emulators-dev","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."},{"from":"ditto","to":"firecrawl-pdf-inspector","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."},{"from":"ditto","to":"box","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."},{"from":"ditto","to":"sazabi","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."}],"signals":[],"claimVerification":[],"explain":{"score":10,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-07-07-ion-design-ditto-site.md\nDitto is an open-source deterministic website cloner from ion.design. Point it at a public URL and it returns a cloned implementation as componentized Next.js or Vite code (Tailwind styling), with marketing copy citing ~5 minutes end-to-end.","at":"2026-07-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"MCP server — https://api.ditto.site/mcp with API key for Claude/Cursor/agent loops.","at":"2026-07-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Hosted REST API — POST https://api.ditto.site/v1/clones, poll job/events, download project (framework: ne","at":"2026-07-07T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.6666666666666666,"contribution":0.06666666666666667,"why":"An MCP surface is declared. An API is declared. Cost is unknown. 2 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.26214289265639185,"contribution":0.036700004971894865,"why":"3 sources cover 1 evidence types. The latest dated evidence is 2026-07-07. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-07-07-ion-design-ditto-site.md\nDitto is an open-source deterministic website cloner from ion.design. Point it at a public URL and it returns a cloned implementation as componentized Next.js or Vite code (Tailwind styling), with marketing copy citing ~5 minutes end-to-end.","at":"2026-07-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"MCP server — https://api.ditto.site/mcp with API key for Claude/Cursor/agent loops.","at":"2026-07-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Hosted REST API — POST https://api.ditto.site/v1/clones, poll job/events, download project (framework: ne","at":"2026-07-07T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["GitHub health: insufficient evidence","Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":10},{"slug":"markitdown","name":"MarkItDown","summary":"MarkItDown (microsoft/markitdown) is a lightweight Python utility that converts many file types to Markdown for LLMs and text-analysis pipelines. README positions it near textract, but focused on preserving structure (headings, lists, tables, links) as Markdown for models rather than high-fidelity human publishing.","kind":"resource","homepage":"https://pypi.org/project/markitdown/","repoUrl":"https://github.com/microsoft/markitdown","docsUrl":"https://learn.microsoft.com/azure/ai-services/content-understanding/","publisher":"","hasMcp":true,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["connect"],"functionProbabilities":[],"slices":[{"functionId":"connect","label":"Connect","note":"MarkItDown (microsoft/markitdown) is a lightweight Python utility that converts many file types to Markdown for LLMs and text-analysis pipelines. README positions it near textract, but focused on preserving structure (headings, lists, tables, links) as Markdown for models rather than high-fidelity human publishing.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-07-microsoft-markitdown.md\nMarkItDown (microsoft/markitdown) is a lightweight Python utility that converts many file types to Markdown for LLMs and text-analysis pipelines. README positions it near textract, but focused on preserving structure (headings, lists, tables, links) as Markdown for models rather than high-fidelity human publishing.","at":"2026-09-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"for image descriptions, 3rd-party plugins (#markitdown-plugin), and an in-repo markitdown-mcp package (PyPI alpha 0.0.1a4 at capture).","at":"2026-09-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Surfaces: CLI (markitdown path > out.md), Python API (MarkItDown().convert(...)), Docker example, optio","at":"2026-09-07T00:00:00.000Z"}],"interfaces":[{"kind":"mcp"},{"kind":"cli"}],"origin":"seed","notes":[],"createdAt":"2026-09-07T00:00:00.000Z","updatedAt":"2026-09-07T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_markitdown","claims":{"name":"MarkItDown","summary":"MarkItDown (microsoft/markitdown) is a lightweight Python utility that converts many file types to Markdown for LLMs and text-analysis pipelines. README positions it near textract, but focused on preserving structure (headings, lists, tables, links) as Markdown for models rather than high-fidelity human publishing.","kind":"resource","publisher":"","homepage":"https://pypi.org/project/markitdown/","repoUrl":"https://github.com/microsoft/markitdown","docsUrl":"https://learn.microsoft.com/azure/ai-services/content-understanding/","costRange":"unknown","functions":["connect"],"slices":[{"functionId":"connect","label":"Connect","note":"MarkItDown (microsoft/markitdown) is a lightweight Python utility that converts many file types to Markdown for LLMs and text-analysis pipelines. README positions it near textract, but focused on preserving structure (headings, lists, tables, links) as Markdown for models rather than high-fidelity human publishing.","cost":"unknown"}],"interfaces":[{"kind":"mcp"},{"kind":"cli"}],"composabilityRationale":""},"relations":[{"from":"markitdown","to":"agentation","kind":"alternative-to","note":"Shared functions connect. Same kind and overlapping capability."},{"from":"markitdown","to":"is-agentic","kind":"alternative-to","note":"Shared functions connect. Same kind and overlapping capability."},{"from":"markitdown","to":"clapper","kind":"alternative-to","note":"Shared functions connect. Same kind and overlapping capability."},{"from":"markitdown","to":"codex-security-plugin","kind":"alternative-to","note":"Shared functions connect. Same kind and overlapping capability."},{"from":"markitdown","to":"container","kind":"alternative-to","note":"Shared functions connect. Same kind and overlapping capability."},{"from":"markitdown","to":"slackhq-nebula","kind":"alternative-to","note":"Shared functions connect. Same kind and overlapping capability."},{"from":"markitdown","to":"cloudflare-quick-tunnels","kind":"alternative-to","note":"Shared functions connect. Same kind and overlapping capability."},{"from":"markitdown","to":"company-brain","kind":"alternative-to","note":"Shared functions connect. Same kind and overlapping capability."}],"signals":[{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-09-07T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":10,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-07-microsoft-markitdown.md\nMarkItDown (microsoft/markitdown) is a lightweight Python utility that converts many file types to Markdown for LLMs and text-analysis pipelines. README positions it near textract, but focused on preserving structure (headings, lists, tables, links) as Markdown for models rather than high-fidelity human publishing.","at":"2026-09-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"for image descriptions, 3rd-party plugins (#markitdown-plugin), and an in-repo markitdown-mcp package (PyPI alpha 0.0.1a4 at capture).","at":"2026-09-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Surfaces: CLI (markitdown path > out.md), Python API (MarkItDown().convert(...)), Docker example, optio","at":"2026-09-07T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.3333333333333333,"contribution":0.03333333333333333,"why":"An MCP surface is declared. No API is declared. Cost is unknown. 1 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.26214289265639185,"contribution":0.036700004971894865,"why":"3 sources cover 1 evidence types. The latest dated evidence is 2026-09-07. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-07-microsoft-markitdown.md\nMarkItDown (microsoft/markitdown) is a lightweight Python utility that converts many file types to Markdown for LLMs and text-analysis pipelines. README positions it near textract, but focused on preserving structure (headings, lists, tables, links) as Markdown for models rather than high-fidelity human publishing.","at":"2026-09-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"for image descriptions, 3rd-party plugins (#markitdown-plugin), and an in-repo markitdown-mcp package (PyPI alpha 0.0.1a4 at capture).","at":"2026-09-07T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Surfaces: CLI (markitdown path > out.md), Python API (MarkItDown().convert(...)), Docker example, optio","at":"2026-09-07T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":10},{"slug":"how-hopx-achieves-100ms-cold-starts","name":"How HopX Achieves 100ms Cold Starts","summary":"# How HopX Achieves 100ms Cold Starts","publisher":"hopx.ai","homepage":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","kind":"resource","hasApi":true,"hasMcp":false,"costRange":"usage","costNotes":"Cost range usage taken from intake evidence.","functions":["auth","code","memory","monitor","store"],"slices":[{"functionId":"auth","label":"auth","note":"Inferred from executor","cost":"Unknown"},{"functionId":"code","label":"code","note":"Inferred from executor","cost":"Unknown"},{"functionId":"memory","label":"memory","note":"Inferred from executor","cost":"Unknown"},{"functionId":"monitor","label":"monitor","note":"Inferred from executor","cost":"Unknown"},{"functionId":"store","label":"store","note":"Inferred from executor","cost":"Unknown"}],"interfaces":[{"kind":"http"}],"composabilityRationale":"Heuristic from executor evidence. Grok pass was unavailable or incomplete. No usage metrics were observed.","signals":[],"functionProbabilities":[{"functionId":"auth","value":0.8,"source":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"lexical","observedAt":"2026-10-17T08:20:54.629Z"},{"functionId":"code","value":0.8,"source":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"lexical","observedAt":"2026-10-17T08:20:54.629Z"},{"functionId":"memory","value":0.8,"source":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"lexical","observedAt":"2026-10-17T08:20:54.629Z"},{"functionId":"monitor","value":0.8,"source":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"lexical","observedAt":"2026-10-17T08:20:54.629Z"},{"functionId":"store","value":0.8,"source":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"lexical","observedAt":"2026-10-17T08:20:54.629Z"}],"claimVerification":[{"key":"mcp","status":"unverified","asserted":"false","evidenceSource":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"fallback"},{"key":"api","status":"unverified","asserted":"true","evidenceSource":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"fallback"},{"key":"cost","status":"unverified","asserted":"usage","evidenceSource":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"fallback"},{"key":"license","status":"unverified","asserted":"","evidenceSource":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","method":"fallback"}],"tweets":[],"notes":[],"origin":"intake","createdAt":"2026-10-17T08:20:55.491Z","updatedAt":"2026-10-17T08:20:55.491Z","sources":[{"kind":"web","label":"executor","url":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","excerpt":"Back to Blog\n\n# How HopX Achieves 100ms Cold Starts\n\nWhen developers hear \"virtual machine,\" they think of slow boot times—30 seconds to minutes. Containers are faster but still take seconds. HopX sandboxes start in under 100 milliseconds.\n","at":"2026-10-17T08:20:55.491Z"}],"recordId":"cmp_how-hopx-achieves-100ms-cold-starts","claims":{"name":"How HopX Achieves 100ms Cold Starts","summary":"# How HopX Achieves 100ms Cold Starts","kind":"resource","publisher":"hopx.ai","homepage":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","costRange":"usage","costNotes":"Cost range usage taken from intake evidence.","functions":["auth","code","memory","monitor","store"],"slices":[{"functionId":"auth","label":"auth","note":"Inferred from executor","cost":"Unknown"},{"functionId":"code","label":"code","note":"Inferred from executor","cost":"Unknown"},{"functionId":"memory","label":"memory","note":"Inferred from executor","cost":"Unknown"},{"functionId":"monitor","label":"monitor","note":"Inferred from executor","cost":"Unknown"},{"functionId":"store","label":"store","note":"Inferred from executor","cost":"Unknown"}],"interfaces":[{"kind":"http"}],"composabilityRationale":"Heuristic from executor evidence. Grok pass was unavailable or incomplete. No usage metrics were observed."},"relations":[{"from":"how-hopx-achieves-100ms-cold-starts","to":"paseo","kind":"fills-same-slot-as","note":"Shared functions code, monitor. Can fill the same function slot."},{"from":"how-hopx-achieves-100ms-cold-starts","to":"comparing-ai-agent-sandbox-platforms-e2b-modal-daytona-and-more","kind":"fills-same-slot-as","note":"Shared functions code, memory, monitor. Can fill the same function slot."},{"from":"how-hopx-achieves-100ms-cold-starts","to":"agentmemory","kind":"fills-same-slot-as","note":"Shared functions code, memory. Can fill the same function slot."},{"from":"how-hopx-achieves-100ms-cold-starts","to":"ai-agent-sandbox-comparison-2026-seven-platforms","kind":"fills-same-slot-as","note":"Shared functions auth, code, memory. Can fill the same function slot."},{"from":"how-hopx-achieves-100ms-cold-starts","to":"daytona-alternatives-4-ai-agent-sandbox-platforms-compared-2026","kind":"fills-same-slot-as","note":"Shared functions code, memory, store. Can fill the same function slot."},{"from":"how-hopx-achieves-100ms-cold-starts","to":"turbopuffer","kind":"fills-same-slot-as","note":"Shared functions memory, store. Can fill the same function slot."},{"from":"how-hopx-achieves-100ms-cold-starts","to":"vellum-assistant","kind":"fills-same-slot-as","note":"Shared functions auth, memory. Can fill the same function slot."},{"from":"how-hopx-achieves-100ms-cold-starts","to":"agent-sandbox","kind":"fills-same-slot-as","note":"Shared functions code, store. Can fill the same function slot."}],"explain":{"score":9,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.6666666666666666,"contribution":0.06666666666666667,"why":"No MCP surface is declared. An API is declared. Cost is usage. 2 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-10-17. Freshness is omitted unless observed as a signal.","sources":[{"kind":"web","label":"executor","url":"https://hopx.ai/blog/deep-dives/how-hopx-achieves-100ms-cold-starts","excerpt":"Back to Blog\n\n# How HopX Achieves 100ms Cold Starts\n\nWhen developers hear \"virtual machine,\" they think of slow boot times—30 seconds to minutes. Containers are faster but still take seconds. HopX sandboxes start in under 100 milliseconds.\n","at":"2026-10-17T08:20:55.491Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["GitHub health: insufficient evidence","Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":9},{"slug":"magika","name":"Magika","summary":"Magika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","kind":"resource","homepage":"https://pypi.org/project/magika/","repoUrl":"https://github.com/google/magika","docsUrl":"https://securityresearch.google/magika/","publisher":"","license":"Apache-2.0","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["test","route"],"functionProbabilities":[{"functionId":"test","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-09-08-google-magika.md","method":"lexical","observedAt":"2026-09-08T00:00:00.000Z"},{"functionId":"route","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-09-08-google-magika.md","method":"lexical","observedAt":"2026-09-08T00:00:00.000Z"}],"slices":[{"functionId":"test","label":"Test","note":"Magika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","cost":"unknown"},{"functionId":"route","label":"Route","note":"Magika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-08-google-magika.md\nMagika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","at":"2026-09-08T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Surfaces: Rust CLI; Python API; JS/TS npm (browser demo); Go WIP; Homebrew / cargo install magika-cli.","at":"2026-09-08T00:00:00.000Z"}],"interfaces":[{"kind":"cli"}],"origin":"seed","notes":[],"createdAt":"2026-09-08T00:00:00.000Z","updatedAt":"2026-09-08T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_magika","claims":{"name":"Magika","summary":"Magika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","kind":"resource","publisher":"","homepage":"https://pypi.org/project/magika/","repoUrl":"https://github.com/google/magika","docsUrl":"https://securityresearch.google/magika/","license":"Apache-2.0","costRange":"unknown","functions":["test","route"],"slices":[{"functionId":"test","label":"Test","note":"Magika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","cost":"unknown"},{"functionId":"route","label":"Route","note":"Magika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","cost":"unknown"}],"interfaces":[{"kind":"cli"}],"composabilityRationale":""},"relations":[{"from":"magika","to":"fix-cold-start-latency-in-ai-sandboxes-techniques","kind":"fills-same-slot-as","note":"Shared functions route, test. Can fill the same function slot."},{"from":"magika","to":"best-code-execution-sandbox-for-ai-agents-in-2026","kind":"fills-same-slot-as","note":"Shared functions route, test. Can fill the same function slot."},{"from":"magika","to":"onyx","kind":"fills-same-slot-as","note":"Shared functions route, test. Can fill the same function slot."}],"signals":[{"key":"has_license","value":1,"source":"component-record","method":"declared-license","observedAt":"2026-09-08T00:00:00.000Z"},{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-09-08T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":9,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.3,"contribution":0.054,"why":"A licence is declared. Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-08-google-magika.md\nMagika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","at":"2026-09-08T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Surfaces: Rust CLI; Python API; JS/TS npm (browser demo); Go WIP; Homebrew / cargo install magika-cli.","at":"2026-09-08T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.22849520230941842,"contribution":0.031989328323318585,"why":"2 sources cover 1 evidence types. The latest dated evidence is 2026-09-08. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-08-google-magika.md\nMagika (google/magika) is Google’s AI-powered file content-type detector: it classifies files from byte content (not just extensions / magic bytes), locally, in milliseconds on CPU. First-party README: ~100M-sample training, 200+ content types, ~99% avg precision/recall on their test set; used at scale for routing Gmail/Drive/Safe Browsing samples to scanners; also integrated with VirusTotal and abuse.ch (README claims).","at":"2026-09-08T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Surfaces: Rust CLI; Python API; JS/TS npm (browser demo); Go WIP; Homebrew / cargo install magika-cli.","at":"2026-09-08T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":9},{"slug":"opendisk","name":"OpenDisk","summary":"OpenDisk is a native macOS disk-space analyzer. README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","kind":"resource","homepage":"https://opendisk.app","repoUrl":"https://github.com/137137137/OpenDisk","publisher":"","license":"MIT","hasMcp":false,"hasApi":false,"costRange":"free","costNotes":"README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","composabilityRationale":"","functions":["stream"],"functionProbabilities":[{"functionId":"stream","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-09-23-137137137-opendisk.md","method":"lexical","observedAt":"2026-09-23T00:00:00.000Z"}],"slices":[{"functionId":"stream","label":"Stream","note":"OpenDisk is a native macOS disk-space analyzer. README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","cost":"free"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-23-137137137-opendisk.md\nOpenDisk is a native macOS disk-space analyzer. README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","at":"2026-09-23T00:00:00.000Z"}],"interfaces":[],"origin":"seed","notes":[],"createdAt":"2026-09-23T00:00:00.000Z","updatedAt":"2026-09-23T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_opendisk","claims":{"name":"OpenDisk","summary":"OpenDisk is a native macOS disk-space analyzer. README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","kind":"resource","publisher":"","homepage":"https://opendisk.app","repoUrl":"https://github.com/137137137/OpenDisk","license":"MIT","costRange":"free","costNotes":"README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","functions":["stream"],"slices":[{"functionId":"stream","label":"Stream","note":"OpenDisk is a native macOS disk-space analyzer. README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","cost":"free"}],"interfaces":[],"composabilityRationale":""},"relations":[{"from":"opendisk","to":"box","kind":"alternative-to","note":"Shared functions stream. Same kind and overlapping capability."},{"from":"opendisk","to":"generative-loaders","kind":"alternative-to","note":"Shared functions stream. Same kind and overlapping capability."}],"signals":[{"key":"has_license","value":1,"source":"component-record","method":"declared-license","observedAt":"2026-09-23T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":9,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"A licence is declared.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-23-137137137-opendisk.md\nOpenDisk is a native macOS disk-space analyzer. README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","at":"2026-09-23T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.3333333333333333,"contribution":0.03333333333333333,"why":"No MCP surface is declared. No API is declared. Cost is free. 1 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-09-23. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-23-137137137-opendisk.md\nOpenDisk is a native macOS disk-space analyzer. README positions it as a fast, free, open-source DaisyDisk alternative: whole drive as an interactive sunburst (hover size, click to zoom), sortable Finder-style list, live streaming scan, incremental rescans, APFS volume groups / firmlinks / purgeable awareness, Collector (drag then delete), Sparkle auto-update.","at":"2026-09-23T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":9},{"slug":"telemetry-dev","name":"telemetry.dev","summary":"Hosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","kind":"resource","homepage":"https://telemetry.dev/","repoUrl":"https://github.com/telemetry-dev/telemetry.dev","docsUrl":"https://docs.telemetry.dev/","publisher":"","hasMcp":false,"hasApi":true,"costRange":"unknown","composabilityRationale":"","functions":["ingest","observe","retrieve"],"functionProbabilities":[{"functionId":"ingest","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-08-24-telemetry-dev.md","method":"lexical","observedAt":"2026-08-24T00:00:00.000Z"},{"functionId":"observe","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-08-24-telemetry-dev.md","method":"lexical","observedAt":"2026-08-24T00:00:00.000Z"},{"functionId":"retrieve","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-08-24-telemetry-dev.md","method":"lexical","observedAt":"2026-08-24T00:00:00.000Z"}],"slices":[{"functionId":"ingest","label":"Ingest","note":"Hosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","cost":"unknown"},{"functionId":"observe","label":"Observe","note":"Hosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","cost":"unknown"},{"functionId":"retrieve","label":"Retrieve","note":"Hosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-24-telemetry-dev.md\nHosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","at":"2026-08-24T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Ingest via TypeScript or Python SDKs, or any OTLP exporter.","at":"2026-08-24T00:00:00.000Z"}],"interfaces":[{"kind":"sdk"}],"origin":"seed","notes":[],"createdAt":"2026-08-24T00:00:00.000Z","updatedAt":"2026-08-24T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_telemetry-dev","claims":{"name":"telemetry.dev","summary":"Hosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","kind":"resource","publisher":"","homepage":"https://telemetry.dev/","repoUrl":"https://github.com/telemetry-dev/telemetry.dev","docsUrl":"https://docs.telemetry.dev/","costRange":"unknown","functions":["ingest","observe","retrieve"],"slices":[{"functionId":"ingest","label":"Ingest","note":"Hosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","cost":"unknown"},{"functionId":"observe","label":"Observe","note":"Hosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","cost":"unknown"},{"functionId":"retrieve","label":"Retrieve","note":"Hosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","cost":"unknown"}],"interfaces":[{"kind":"sdk"}],"composabilityRationale":""},"relations":[],"signals":[{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-08-24T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":9,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-24-telemetry-dev.md\nHosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","at":"2026-08-24T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Ingest via TypeScript or Python SDKs, or any OTLP exporter.","at":"2026-08-24T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.3333333333333333,"contribution":0.03333333333333333,"why":"No MCP surface is declared. An API is declared. Cost is unknown. 1 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.22849520230941842,"contribution":0.031989328323318585,"why":"2 sources cover 1 evidence types. The latest dated evidence is 2026-08-24. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-24-telemetry-dev.md\nHosted observability for AI/LLM apps. Product line: every model call, tool step, and retrieval in one OpenTelemetry trace, with tokens, cost, latency, and errors. Ingest via TypeScript or Python SDKs, or any OTLP exporter. Cost is computed server-side against 4700+ models.","at":"2026-08-24T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"Ingest via TypeScript or Python SDKs, or any OTLP exporter.","at":"2026-08-24T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":9},{"slug":"generative-loaders","name":"Generative Loaders","summary":"Generative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","kind":"resource","homepage":"https://generativeloaders.com/","repoUrl":"https://github.com/kasturikhanke/generative-loaders","docsUrl":"https://generativeloaders.com/docs","publisher":"","license":"MIT","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["generate","stream"],"functionProbabilities":[{"functionId":"generate","value":0.72,"source":"06 Knowledge Library/Resources/design/2026-08-09-kasturi-khanke-generative-loaders.md","method":"lexical","observedAt":"2026-08-09T00:00:00.000Z"},{"functionId":"stream","value":0.72,"source":"06 Knowledge Library/Resources/design/2026-08-09-kasturi-khanke-generative-loaders.md","method":"lexical","observedAt":"2026-08-09T00:00:00.000Z"}],"slices":[{"functionId":"generate","label":"Generate","note":"Generative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","cost":"unknown"},{"functionId":"stream","label":"Stream","note":"Generative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-09-kasturi-khanke-generative-loaders.md\nGenerative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","at":"2026-08-09T00:00:00.000Z"}],"interfaces":[],"origin":"seed","notes":[],"createdAt":"2026-08-09T00:00:00.000Z","updatedAt":"2026-08-09T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_generative-loaders","claims":{"name":"Generative Loaders","summary":"Generative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","kind":"resource","publisher":"","homepage":"https://generativeloaders.com/","repoUrl":"https://github.com/kasturikhanke/generative-loaders","docsUrl":"https://generativeloaders.com/docs","license":"MIT","costRange":"unknown","functions":["generate","stream"],"slices":[{"functionId":"generate","label":"Generate","note":"Generative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","cost":"unknown"},{"functionId":"stream","label":"Stream","note":"Generative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","cost":"unknown"}],"interfaces":[],"composabilityRationale":""},"relations":[{"from":"generative-loaders","to":"opendisk","kind":"alternative-to","note":"Shared functions stream. Same kind and overlapping capability."}],"signals":[{"key":"has_license","value":1,"source":"component-record","method":"declared-license","observedAt":"2026-08-09T00:00:00.000Z"},{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-08-09T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":8,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.3,"contribution":0.054,"why":"A licence is declared. Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-09-kasturi-khanke-generative-loaders.md\nGenerative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","at":"2026-08-09T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-08-09. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-09-kasturi-khanke-generative-loaders.md\nGenerative Loaders is an MIT-licensed React package and live gallery for loading states specific to generative interfaces: streaming-text reveals, compact inline activity indicators, and image-generation placeholders. Install with npm install generative-loaders; it supports React 18+ and uses Framer Motion.","at":"2026-08-09T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":8},{"slug":"victoriametrics","name":"VictoriaMetrics","summary":"VictoriaMetrics develops separate storage/query components for the three primary OpenTelemetry signals: - VictoriaMetrics for time-series metrics; - VictoriaLogs for logs; and - VictoriaTraces for traces. Its current documentation says each component accepts OpenTelemetry data natively and can sit behind instrumented applications or an OpenTelemetry Collector.","kind":"resource","homepage":"https://victoriametrics.com/","repoUrl":"https://github.com/VictoriaMetrics/ai-observability","docsUrl":"https://docs.victoriametrics.com/","publisher":"","license":"Apache-2.0","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["store"],"functionProbabilities":[{"functionId":"store","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-08-04-victoriametrics-observability-stack.md","method":"lexical","observedAt":"2026-08-04T00:00:00.000Z"}],"slices":[{"functionId":"store","label":"Store","note":"VictoriaMetrics develops separate storage/query components for the three primary OpenTelemetry signals: - VictoriaMetrics for time-series metrics; - VictoriaLogs for logs; and - VictoriaTraces for traces. Its current documentation says each component accepts OpenTelemetry data natively and can sit behind instrumented applications or an OpenTelemetry Collector.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-04-victoriametrics-observability-stack.md\nVictoriaMetrics develops separate storage/query components for the three primary OpenTelemetry signals: - VictoriaMetrics for time-series metrics; - VictoriaLogs for logs; and - VictoriaTraces for traces. Its current documentation says each component accepts OpenTelemetry data natively and can sit behind instrumented applications or an OpenTelemetry Collector.","at":"2026-08-04T00:00:00.000Z"}],"interfaces":[],"origin":"seed","notes":[],"createdAt":"2026-08-04T00:00:00.000Z","updatedAt":"2026-08-04T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_victoriametrics","claims":{"name":"VictoriaMetrics","summary":"VictoriaMetrics develops separate storage/query components for the three primary OpenTelemetry signals: - VictoriaMetrics for time-series metrics; - VictoriaLogs for logs; and - VictoriaTraces for traces. Its current documentation says each component accepts OpenTelemetry data natively and can sit behind instrumented applications or an OpenTelemetry Collector.","kind":"resource","publisher":"","homepage":"https://victoriametrics.com/","repoUrl":"https://github.com/VictoriaMetrics/ai-observability","docsUrl":"https://docs.victoriametrics.com/","license":"Apache-2.0","costRange":"unknown","functions":["store"],"slices":[{"functionId":"store","label":"Store","note":"VictoriaMetrics develops separate storage/query components for the three primary OpenTelemetry signals: - VictoriaMetrics for time-series metrics; - VictoriaLogs for logs; and - VictoriaTraces for traces. Its current documentation says each component accepts OpenTelemetry data natively and can sit behind instrumented applications or an OpenTelemetry Collector.","cost":"unknown"}],"interfaces":[],"composabilityRationale":""},"relations":[{"from":"victoriametrics","to":"pgbot","kind":"alternative-to","note":"Shared functions store. Same kind and overlapping capability."}],"signals":[{"key":"has_license","value":1,"source":"component-record","method":"declared-license","observedAt":"2026-08-04T00:00:00.000Z"},{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-08-04T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":8,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.3,"contribution":0.054,"why":"A licence is declared. Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-04-victoriametrics-observability-stack.md\nVictoriaMetrics develops separate storage/query components for the three primary OpenTelemetry signals: - VictoriaMetrics for time-series metrics; - VictoriaLogs for logs; and - VictoriaTraces for traces. Its current documentation says each component accepts OpenTelemetry data natively and can sit behind instrumented applications or an OpenTelemetry Collector.","at":"2026-08-04T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-08-04. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-08-04-victoriametrics-observability-stack.md\nVictoriaMetrics develops separate storage/query components for the three primary OpenTelemetry signals: - VictoriaMetrics for time-series metrics; - VictoriaLogs for logs; and - VictoriaTraces for traces. Its current documentation says each component accepts OpenTelemetry data natively and can sit behind instrumented applications or an OpenTelemetry Collector.","at":"2026-08-04T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":8},{"slug":"railcode","name":"Railcode","summary":"Railcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","kind":"resource","homepage":"https://railcode.dev/","repoUrl":"https://github.com/Railcode-HQ","publisher":"","hasMcp":true,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["auth","deploy","tool-call"],"functionProbabilities":[{"functionId":"auth","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-09-10-railcode-dev.md","method":"lexical","observedAt":"2026-09-10T00:00:00.000Z"},{"functionId":"deploy","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-09-10-railcode-dev.md","method":"lexical","observedAt":"2026-09-10T00:00:00.000Z"},{"functionId":"tool-call","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-09-10-railcode-dev.md","method":"lexical","observedAt":"2026-09-10T00:00:00.000Z"}],"slices":[{"functionId":"auth","label":"Auth","note":"Railcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","cost":"unknown"},{"functionId":"deploy","label":"Deploy","note":"Railcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","cost":"unknown"},{"functionId":"tool-call","label":"Tool-call","note":"Railcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-10-railcode-dev.md\nRailcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","at":"2026-09-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"v blog, 2026-09-01): no in-product agent on purpose — “best harness is your own harness”; MCP/CLI over embedded chat.","at":"2026-09-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"v blog, 2026-09-01): no in-product agent on purpose — “best harness is your own harness”; MCP/CLI over embedded chat.","at":"2026-09-10T00:00:00.000Z"}],"interfaces":[{"kind":"mcp"},{"kind":"cli"}],"origin":"seed","notes":[],"createdAt":"2026-09-10T00:00:00.000Z","updatedAt":"2026-09-10T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_railcode","claims":{"name":"Railcode","summary":"Railcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","kind":"resource","publisher":"","homepage":"https://railcode.dev/","repoUrl":"https://github.com/Railcode-HQ","costRange":"unknown","functions":["auth","deploy","tool-call"],"slices":[{"functionId":"auth","label":"Auth","note":"Railcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","cost":"unknown"},{"functionId":"deploy","label":"Deploy","note":"Railcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","cost":"unknown"},{"functionId":"tool-call","label":"Tool-call","note":"Railcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","cost":"unknown"}],"interfaces":[{"kind":"mcp"},{"kind":"cli"}],"composabilityRationale":""},"relations":[{"from":"railcode","to":"openship","kind":"fills-same-slot-as","note":"Shared functions deploy, tool-call. Can fill the same function slot."},{"from":"railcode","to":"vellum-assistant","kind":"fills-same-slot-as","note":"Shared functions auth, tool-call. Can fill the same function slot."},{"from":"railcode","to":"agent-sandbox","kind":"fills-same-slot-as","note":"Shared functions deploy, tool-call. Can fill the same function slot."},{"from":"railcode","to":"ai-agent-sandbox-comparison-2026-seven-platforms","kind":"fills-same-slot-as","note":"Shared functions auth, deploy. Can fill the same function slot."}],"signals":[],"claimVerification":[],"explain":{"score":7,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-10-railcode-dev.md\nRailcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","at":"2026-09-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"v blog, 2026-09-01): no in-product agent on purpose — “best harness is your own harness”; MCP/CLI over embedded chat.","at":"2026-09-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"v blog, 2026-09-01): no in-product agent on purpose — “best harness is your own harness”; MCP/CLI over embedded chat.","at":"2026-09-10T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.3333333333333333,"contribution":0.03333333333333333,"why":"An MCP surface is declared. No API is declared. Cost is unknown. 1 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.26214289265639185,"contribution":0.036700004971894865,"why":"3 sources cover 1 evidence types. The latest dated evidence is 2026-09-10. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-10-railcode-dev.md\nRailcode is Yakko Majuri’s secure / governed cloud for internal software — apps and agents (“internal Vercel” framing on the launch post). Build with your own tools; deploy into a company-governed sandbox with auth, permissions, data, and connectors centralized.","at":"2026-09-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"v blog, 2026-09-01): no in-product agent on purpose — “best harness is your own harness”; MCP/CLI over embedded chat.","at":"2026-09-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"v blog, 2026-09-01): no in-product agent on purpose — “best harness is your own harness”; MCP/CLI over embedded chat.","at":"2026-09-10T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["GitHub health: insufficient evidence","Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":7},{"slug":"rea","name":"REA","summary":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","kind":"resource","homepage":"https://rea.tools/","repoUrl":"https://github.com/morluto/rea","publisher":"","hasMcp":true,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["code","test","connect"],"functionProbabilities":[{"functionId":"code","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-10-10-morluto-rea.md","method":"lexical","observedAt":"2026-10-10T00:00:00.000Z"},{"functionId":"test","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-10-10-morluto-rea.md","method":"lexical","observedAt":"2026-10-10T00:00:00.000Z"},{"functionId":"connect","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-10-10-morluto-rea.md","method":"lexical","observedAt":"2026-10-10T00:00:00.000Z"}],"slices":[{"functionId":"code","label":"Code","note":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","cost":"unknown"},{"functionId":"test","label":"Test","note":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","cost":"unknown"},{"functionId":"connect","label":"Connect","note":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-10-10-morluto-rea.md\nREADME tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","at":"2026-10-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls","at":"2026-10-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"The CLI uses the same workflows.","at":"2026-10-10T00:00:00.000Z"}],"interfaces":[{"kind":"mcp"},{"kind":"cli"}],"origin":"seed","notes":[],"createdAt":"2026-10-10T00:00:00.000Z","updatedAt":"2026-10-10T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_rea","claims":{"name":"REA","summary":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","kind":"resource","publisher":"","homepage":"https://rea.tools/","repoUrl":"https://github.com/morluto/rea","costRange":"unknown","functions":["code","test","connect"],"slices":[{"functionId":"code","label":"Code","note":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","cost":"unknown"},{"functionId":"test","label":"Test","note":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","cost":"unknown"},{"functionId":"connect","label":"Connect","note":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","cost":"unknown"}],"interfaces":[{"kind":"mcp"},{"kind":"cli"}],"composabilityRationale":""},"relations":[{"from":"rea","to":"executor","kind":"fills-same-slot-as","note":"Shared functions code, connect. Can fill the same function slot."},{"from":"rea","to":"agentmemory","kind":"alternative-to","note":"Shared functions code, connect. Same kind and overlapping capability."},{"from":"rea","to":"rtk","kind":"fills-same-slot-as","note":"Shared functions code, test. Can fill the same function slot."},{"from":"rea","to":"onyx","kind":"fills-same-slot-as","note":"Shared functions code, connect, test. Can fill the same function slot."},{"from":"rea","to":"pen-dev","kind":"fills-same-slot-as","note":"Shared functions code, connect. Can fill the same function slot."},{"from":"rea","to":"comparing-ai-agent-sandbox-platforms-e2b-modal-daytona-and-more","kind":"fills-same-slot-as","note":"Shared functions code, connect. Can fill the same function slot."},{"from":"rea","to":"fix-cold-start-latency-in-ai-sandboxes-techniques","kind":"fills-same-slot-as","note":"Shared functions code, test. Can fill the same function slot."},{"from":"rea","to":"ai-agent-sandbox-comparison-2026-seven-platforms","kind":"fills-same-slot-as","note":"Shared functions code, test. Can fill the same function slot."}],"signals":[],"claimVerification":[],"explain":{"score":7,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-10-10-morluto-rea.md\nREADME tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","at":"2026-10-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls","at":"2026-10-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"The CLI uses the same workflows.","at":"2026-10-10T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.3333333333333333,"contribution":0.03333333333333333,"why":"An MCP surface is declared. No API is declared. Cost is unknown. 1 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.26214289265639185,"contribution":0.036700004971894865,"why":"3 sources cover 1 evidence types. The latest dated evidence is 2026-10-10. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-10-10-morluto-rea.md\nREADME tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls REA through MCP to inspect a local target and trace relevant code; REA returns findings with their evidence, and the agent uses them to explain the behavior or write and test an implementation.","at":"2026-10-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"README tagline: \"One MCP for reverse engineering across binaries, applications, and runtime behavior.\" The agent calls","at":"2026-10-10T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"The CLI uses the same workflows.","at":"2026-10-10T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["GitHub health: insufficient evidence","Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":7},{"slug":"rikyu","name":"Rikyū","summary":"Rikyū (named for the tea master) is an AI design SaaS: describe what you need in a sentence and it generates a coherent brand/asset set — logo, web, social, print — carried across one visual identity. Positioning: \"skip the design work\" — no design skills, no asset hunting, one design language across everything that follows.","kind":"resource","homepage":"https://rikyu.ai/","publisher":"","hasMcp":true,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["identity"],"functionProbabilities":[{"functionId":"identity","value":0.8,"source":"06 Knowledge Library/Resources/design/2026-08-11-rikyu-ai.md","method":"lexical","observedAt":"2026-08-11T00:00:00.000Z"}],"slices":[{"functionId":"identity","label":"Identity","note":"Rikyū (named for the tea master) is an AI design SaaS: describe what you need in a sentence and it generates a coherent brand/asset set — logo, web, social, print — carried across one visual identity. Positioning: \"skip the design work\" — no design skills, no asset hunting, one design language across everything that follows.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-11-rikyu-ai.md\nRikyū (named for the tea master) is an AI design SaaS: describe what you need in a sentence and it generates a coherent brand/asset set — logo, web, social, print — carried across one visual identity. Positioning: \"skip the design work\" — no design skills, no asset hunting, one design language across everything that follows.","at":"2026-08-11T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"- MCP integration: connect Claude, Codex, etc.","at":"2026-08-11T00:00:00.000Z"}],"interfaces":[{"kind":"mcp"}],"origin":"seed","notes":[],"createdAt":"2026-08-11T00:00:00.000Z","updatedAt":"2026-08-11T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_rikyu","claims":{"name":"Rikyū","summary":"Rikyū (named for the tea master) is an AI design SaaS: describe what you need in a sentence and it generates a coherent brand/asset set — logo, web, social, print — carried across one visual identity. Positioning: \"skip the design work\" — no design skills, no asset hunting, one design language across everything that follows.","kind":"resource","publisher":"","homepage":"https://rikyu.ai/","costRange":"unknown","functions":["identity"],"slices":[{"functionId":"identity","label":"Identity","note":"Rikyū (named for the tea master) is an AI design SaaS: describe what you need in a sentence and it generates a coherent brand/asset set — logo, web, social, print — carried across one visual identity. Positioning: \"skip the design work\" — no design skills, no asset hunting, one design language across everything that follows.","cost":"unknown"}],"interfaces":[{"kind":"mcp"}],"composabilityRationale":""},"relations":[],"signals":[],"claimVerification":[],"explain":{"score":7,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-11-rikyu-ai.md\nRikyū (named for the tea master) is an AI design SaaS: describe what you need in a sentence and it generates a coherent brand/asset set — logo, web, social, print — carried across one visual identity. Positioning: \"skip the design work\" — no design skills, no asset hunting, one design language across everything that follows.","at":"2026-08-11T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"- MCP integration: connect Claude, Codex, etc.","at":"2026-08-11T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0.3333333333333333,"contribution":0.03333333333333333,"why":"An MCP surface is declared. No API is declared. Cost is unknown. 1 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.22849520230941842,"contribution":0.031989328323318585,"why":"2 sources cover 1 evidence types. The latest dated evidence is 2026-08-11. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-11-rikyu-ai.md\nRikyū (named for the tea master) is an AI design SaaS: describe what you need in a sentence and it generates a coherent brand/asset set — logo, web, social, print — carried across one visual identity. Positioning: \"skip the design work\" — no design skills, no asset hunting, one design language across everything that follows.","at":"2026-08-11T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"- MCP integration: connect Claude, Codex, etc.","at":"2026-08-11T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["GitHub health: insufficient evidence","Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":7},{"slug":"open-notebook","name":"Open Notebook","summary":"Open Notebook is an open-source implementation of Google NotebookLM-style workflows with more model choice and deployment flexibility. The project positions itself as a private, multi-model, local/self-hostable notebook for ingesting sources, searching them, chatting with grounded context, and generating podcasts from research material.","kind":"resource","homepage":"https://www.open-notebook.ai","repoUrl":"https://github.com/lfnovo/open-notebook","publisher":"","license":"MIT","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["deploy"],"functionProbabilities":[{"functionId":"deploy","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-06-23-lfnovo-open-notebook.md","method":"lexical","observedAt":"2026-06-23T00:00:00.000Z"}],"slices":[{"functionId":"deploy","label":"Deploy","note":"Open Notebook is an open-source implementation of Google NotebookLM-style workflows with more model choice and deployment flexibility. The project positions itself as a private, multi-model, local/self-hostable notebook for ingesting sources, searching them, chatting with grounded context, and generating podcasts from research material.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-06-23-lfnovo-open-notebook.md\nOpen Notebook is an open-source implementation of Google NotebookLM-style workflows with more model choice and deployment flexibility. The project positions itself as a private, multi-model, local/self-hostable notebook for ingesting sources, searching them, chatting with grounded context, and generating podcasts from research material.","at":"2026-06-23T00:00:00.000Z"}],"interfaces":[],"origin":"seed","notes":[],"createdAt":"2026-06-23T00:00:00.000Z","updatedAt":"2026-06-23T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_open-notebook","claims":{"name":"Open Notebook","summary":"Open Notebook is an open-source implementation of Google NotebookLM-style workflows with more model choice and deployment flexibility. The project positions itself as a private, multi-model, local/self-hostable notebook for ingesting sources, searching them, chatting with grounded context, and generating podcasts from research material.","kind":"resource","publisher":"","homepage":"https://www.open-notebook.ai","repoUrl":"https://github.com/lfnovo/open-notebook","license":"MIT","costRange":"unknown","functions":["deploy"],"slices":[{"functionId":"deploy","label":"Deploy","note":"Open Notebook is an open-source implementation of Google NotebookLM-style workflows with more model choice and deployment flexibility. The project positions itself as a private, multi-model, local/self-hostable notebook for ingesting sources, searching them, chatting with grounded context, and generating podcasts from research material.","cost":"unknown"}],"interfaces":[],"composabilityRationale":""},"relations":[],"signals":[{"key":"has_license","value":1,"source":"component-record","method":"declared-license","observedAt":"2026-06-23T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":5,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"A licence is declared.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-06-23-lfnovo-open-notebook.md\nOpen Notebook is an open-source implementation of Google NotebookLM-style workflows with more model choice and deployment flexibility. The project positions itself as a private, multi-model, local/self-hostable notebook for ingesting sources, searching them, chatting with grounded context, and generating podcasts from research material.","at":"2026-06-23T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-06-23. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-06-23-lfnovo-open-notebook.md\nOpen Notebook is an open-source implementation of Google NotebookLM-style workflows with more model choice and deployment flexibility. The project positions itself as a private, multi-model, local/self-hostable notebook for ingesting sources, searching them, chatting with grounded context, and generating podcasts from research material.","at":"2026-06-23T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":5},{"slug":"orgo-ai","name":"Orgo.ai","summary":"The computer underneath the agent. Instant full cloud desktops (GUI, browser, filesystem, terminal, apps) that AI agents can see and control via API — boot claimed under ~500ms. Always-on until stopped. Linux + Windows GA; Mac closed beta. People use it three common ways (docs): 1.","kind":"resource","homepage":"https://orgo.ai","docsUrl":"https://docs.orgo.ai/","publisher":"","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["browser"],"functionProbabilities":[{"functionId":"browser","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-07-21-orgo-ai-cloud-computers-for-agents.md","method":"lexical","observedAt":"2026-07-21T00:00:00.000Z"}],"slices":[{"functionId":"browser","label":"Browser","note":"The computer underneath the agent. Instant full cloud desktops (GUI, browser, filesystem, terminal, apps) that AI agents can see and control via API — boot claimed under ~500ms. Always-on until stopped. Linux + Windows GA; Mac closed beta. People use it three common ways (docs): 1.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-07-21-orgo-ai-cloud-computers-for-agents.md\nThe computer underneath the agent. Instant full cloud desktops (GUI, browser, filesystem, terminal, apps) that AI agents can see and control via API — boot claimed under ~500ms. Always-on until stopped. Linux + Windows GA; Mac closed beta. People use it three common ways (docs): 1.","at":"2026-07-21T00:00:00.000Z"}],"interfaces":[],"origin":"seed","notes":[],"createdAt":"2026-07-21T00:00:00.000Z","updatedAt":"2026-07-21T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_orgo-ai","claims":{"name":"Orgo.ai","summary":"The computer underneath the agent. Instant full cloud desktops (GUI, browser, filesystem, terminal, apps) that AI agents can see and control via API — boot claimed under ~500ms. Always-on until stopped. Linux + Windows GA; Mac closed beta. People use it three common ways (docs): 1.","kind":"resource","publisher":"","homepage":"https://orgo.ai","docsUrl":"https://docs.orgo.ai/","costRange":"unknown","functions":["browser"],"slices":[{"functionId":"browser","label":"Browser","note":"The computer underneath the agent. Instant full cloud desktops (GUI, browser, filesystem, terminal, apps) that AI agents can see and control via API — boot claimed under ~500ms. Always-on until stopped. Linux + Windows GA; Mac closed beta. People use it three common ways (docs): 1.","cost":"unknown"}],"interfaces":[],"composabilityRationale":""},"relations":[{"from":"orgo-ai","to":"smaug","kind":"alternative-to","note":"Shared functions browser. Same kind and overlapping capability."}],"signals":[{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-07-21T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":5,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-07-21-orgo-ai-cloud-computers-for-agents.md\nThe computer underneath the agent. Instant full cloud desktops (GUI, browser, filesystem, terminal, apps) that AI agents can see and control via API — boot claimed under ~500ms. Always-on until stopped. Linux + Windows GA; Mac closed beta. People use it three common ways (docs): 1.","at":"2026-07-21T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-07-21. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-07-21-orgo-ai-cloud-computers-for-agents.md\nThe computer underneath the agent. Instant full cloud desktops (GUI, browser, filesystem, terminal, apps) that AI agents can see and control via API — boot claimed under ~500ms. Always-on until stopped. Linux + Windows GA; Mac closed beta. People use it three common ways (docs): 1.","at":"2026-07-21T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":5},{"slug":"quiverai","name":"QuiverAI","summary":"QuiverAI ships foundational models for generating, editing, and animating editable vector/SVG assets (logos, illustrations, diagrams, line work; typography & animations marked coming soon on marketing site). Arrow 2 is the Sep 2026 model line called out as higher quality and faster, in App and API.","kind":"resource","homepage":"https://quiver.ai/","docsUrl":"https://docs.quiver.ai/","publisher":"","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["embed"],"functionProbabilities":[{"functionId":"embed","value":0.72,"source":"06 Knowledge Library/Resources/design/2026-09-18-quiverai-arrow-2.md","method":"lexical","observedAt":"2026-09-18T00:00:00.000Z"}],"slices":[{"functionId":"embed","label":"Embed","note":"QuiverAI ships foundational models for generating, editing, and animating editable vector/SVG assets (logos, illustrations, diagrams, line work; typography & animations marked coming soon on marketing site). Arrow 2 is the Sep 2026 model line called out as higher quality and faster, in App and API.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-09-18-quiverai-arrow-2.md\nQuiverAI ships foundational models for generating, editing, and animating editable vector/SVG assets (logos, illustrations, diagrams, line work; typography & animations marked coming soon on marketing site). Arrow 2 is the Sep 2026 model line called out as higher quality and faster, in App and API.","at":"2026-09-18T00:00:00.000Z"}],"interfaces":[],"origin":"seed","notes":[],"createdAt":"2026-09-18T00:00:00.000Z","updatedAt":"2026-09-18T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_quiverai","claims":{"name":"QuiverAI","summary":"QuiverAI ships foundational models for generating, editing, and animating editable vector/SVG assets (logos, illustrations, diagrams, line work; typography & animations marked coming soon on marketing site). Arrow 2 is the Sep 2026 model line called out as higher quality and faster, in App and API.","kind":"resource","publisher":"","homepage":"https://quiver.ai/","docsUrl":"https://docs.quiver.ai/","costRange":"unknown","functions":["embed"],"slices":[{"functionId":"embed","label":"Embed","note":"QuiverAI ships foundational models for generating, editing, and animating editable vector/SVG assets (logos, illustrations, diagrams, line work; typography & animations marked coming soon on marketing site). Arrow 2 is the Sep 2026 model line called out as higher quality and faster, in App and API.","cost":"unknown"}],"interfaces":[],"composabilityRationale":""},"relations":[],"signals":[{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-09-18T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":5,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-09-18-quiverai-arrow-2.md\nQuiverAI ships foundational models for generating, editing, and animating editable vector/SVG assets (logos, illustrations, diagrams, line work; typography & animations marked coming soon on marketing site). Arrow 2 is the Sep 2026 model line called out as higher quality and faster, in App and API.","at":"2026-09-18T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-09-18. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-09-18-quiverai-arrow-2.md\nQuiverAI ships foundational models for generating, editing, and animating editable vector/SVG assets (logos, illustrations, diagrams, line work; typography & animations marked coming soon on marketing site). Arrow 2 is the Sep 2026 model line called out as higher quality and faster, in App and API.","at":"2026-09-18T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":5},{"slug":"sazabi","name":"Sazabi","summary":"Sazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","kind":"resource","homepage":"https://www.sazabi.com/","repoUrl":"https://github.com/sazabi","docsUrl":"https://docs.sazabi.com/","publisher":"","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["code","observe"],"functionProbabilities":[{"functionId":"code","value":0.92,"source":"06 Knowledge Library/Resources/coding/2026-09-11-sazabi.md","method":"lexical","observedAt":"2026-09-11T00:00:00.000Z"},{"functionId":"observe","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-09-11-sazabi.md","method":"lexical","observedAt":"2026-09-11T00:00:00.000Z"}],"slices":[{"functionId":"code","label":"Code","note":"Sazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","cost":"unknown"},{"functionId":"observe","label":"Observe","note":"Sazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-11-sazabi.md\nSazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","at":"2026-09-11T00:00:00.000Z"}],"interfaces":[],"origin":"seed","notes":[],"createdAt":"2026-09-11T00:00:00.000Z","updatedAt":"2026-09-11T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_sazabi","claims":{"name":"Sazabi","summary":"Sazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","kind":"resource","publisher":"","homepage":"https://www.sazabi.com/","repoUrl":"https://github.com/sazabi","docsUrl":"https://docs.sazabi.com/","costRange":"unknown","functions":["code","observe"],"slices":[{"functionId":"code","label":"Code","note":"Sazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","cost":"unknown"},{"functionId":"observe","label":"Observe","note":"Sazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","cost":"unknown"}],"interfaces":[],"composabilityRationale":""},"relations":[{"from":"sazabi","to":"ditto","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."},{"from":"sazabi","to":"emulators-dev","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."},{"from":"sazabi","to":"firecrawl-pdf-inspector","kind":"alternative-to","note":"Shared functions code. Same kind and overlapping capability."}],"signals":[{"key":"has_docs","value":1,"source":"component-record","method":"declared-docs","observedAt":"2026-09-11T00:00:00.000Z"}],"claimVerification":[],"explain":{"score":5,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"value":0.15,"contribution":0.027,"why":"Documentation is available.","sources":[],"evidence":"observed"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-11-sazabi.md\nSazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","at":"2026-09-11T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-09-11. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-09-11-sazabi.md\nSazabi is a hosted AI-native engineering observability product. First-party homepage framing (2026-09-11): - Title / OG title: Sazabi | AI-Native Observability - Meta description: Autonomous alerts. Conversational debugging. Coding agent integrations.","at":"2026-09-11T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":5},{"slug":"agentmemory","name":"AgentMemory","summary":"An open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","kind":"resource","repoUrl":"https://github.com/rohitg00/agentmemory","publisher":"","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["code","memory","connect"],"functionProbabilities":[{"functionId":"code","value":0.92,"source":"06 Knowledge Library/Resources/coding/2026-05-08-agentmemory-persistent-memory-for-coding-agents.md","method":"lexical","observedAt":"2026-05-08T00:00:00.000Z"},{"functionId":"memory","value":0.8,"source":"06 Knowledge Library/Resources/coding/2026-05-08-agentmemory-persistent-memory-for-coding-agents.md","method":"lexical","observedAt":"2026-05-08T00:00:00.000Z"},{"functionId":"connect","value":0.72,"source":"06 Knowledge Library/Resources/coding/2026-05-08-agentmemory-persistent-memory-for-coding-agents.md","method":"lexical","observedAt":"2026-05-08T00:00:00.000Z"}],"slices":[{"functionId":"code","label":"Code","note":"An open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","cost":"unknown"},{"functionId":"memory","label":"Memory","note":"An open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","cost":"unknown"},{"functionId":"connect","label":"Connect","note":"An open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-05-08-agentmemory-persistent-memory-for-coding-agents.md\nAn open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","at":"2026-05-08T00:00:00.000Z"}],"interfaces":[],"origin":"seed","notes":[],"createdAt":"2026-05-08T00:00:00.000Z","updatedAt":"2026-05-08T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_agentmemory","claims":{"name":"AgentMemory","summary":"An open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","kind":"resource","publisher":"","repoUrl":"https://github.com/rohitg00/agentmemory","costRange":"unknown","functions":["code","memory","connect"],"slices":[{"functionId":"code","label":"Code","note":"An open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","cost":"unknown"},{"functionId":"memory","label":"Memory","note":"An open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","cost":"unknown"},{"functionId":"connect","label":"Connect","note":"An open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","cost":"unknown"}],"interfaces":[],"composabilityRationale":""},"relations":[{"from":"agentmemory","to":"executor","kind":"fills-same-slot-as","note":"Shared functions code, connect. Can fill the same function slot."},{"from":"agentmemory","to":"rea","kind":"alternative-to","note":"Shared functions code, connect. Same kind and overlapping capability."},{"from":"agentmemory","to":"comparing-ai-agent-sandbox-platforms-e2b-modal-daytona-and-more","kind":"fills-same-slot-as","note":"Shared functions code, connect, memory. Can fill the same function slot."},{"from":"agentmemory","to":"atomic-agent","kind":"fills-same-slot-as","note":"Shared functions connect, memory. Can fill the same function slot."},{"from":"agentmemory","to":"how-hopx-achieves-100ms-cold-starts","kind":"fills-same-slot-as","note":"Shared functions code, memory. Can fill the same function slot."},{"from":"agentmemory","to":"pen-dev","kind":"fills-same-slot-as","note":"Shared functions code, connect. Can fill the same function slot."},{"from":"agentmemory","to":"onyx","kind":"fills-same-slot-as","note":"Shared functions code, connect. Can fill the same function slot."},{"from":"agentmemory","to":"ai-agent-sandbox-comparison-2026-seven-platforms","kind":"fills-same-slot-as","note":"Shared functions code, memory. Can fill the same function slot."}],"signals":[],"claimVerification":[],"explain":{"score":3,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-05-08-agentmemory-persistent-memory-for-coding-agents.md\nAn open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","at":"2026-05-08T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.18107144632819594,"contribution":0.025350002485947435,"why":"1 sources cover 1 evidence types. The latest dated evidence is 2026-05-08. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/coding/2026-05-08-agentmemory-persistent-memory-for-coding-agents.md\nAn open source memory system for coding agents that captures session activity, compresses it into searchable memory, and re-injects relevant context into future sessions. The repo positions it as agent-agnostic infrastructure that can work across Claude Code, OpenClaw, Codex CLI, Cursor, Gemini CLI, and other MCP or HTTP-capable agents.","at":"2026-05-08T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["GitHub health: insufficient evidence","Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":3},{"slug":"transitions-dev","name":"Transitions.dev","summary":"Site title Transitions.dev: UI transitions for AI agents. README: “an interactive collection of reusable CSS transitions. Each card on the index page demonstrates a different interaction pattern and ships a copy-ready, portable CSS snippet.” Live index groups cards as All / Essential / AI Agents / Effects / Texts / Pro.","kind":"resource","homepage":"https://transitions.dev/","repoUrl":"https://github.com/Jakubantalik/transitions.dev","publisher":"","hasMcp":false,"hasApi":false,"costRange":"unknown","composabilityRationale":"","functions":["index"],"functionProbabilities":[{"functionId":"index","value":0.8,"source":"06 Knowledge Library/Resources/design/2026-08-26-transitions-dev.md","method":"lexical","observedAt":"2026-08-26T00:00:00.000Z"}],"slices":[{"functionId":"index","label":"Index","note":"Site title Transitions.dev: UI transitions for AI agents. README: “an interactive collection of reusable CSS transitions. Each card on the index page demonstrates a different interaction pattern and ships a copy-ready, portable CSS snippet.” Live index groups cards as All / Essential / AI Agents / Effects / Texts / Pro.","cost":"unknown"}],"tweets":[],"sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-26-transitions-dev.md\nSite title Transitions.dev: UI transitions for AI agents. README: “an interactive collection of reusable CSS transitions. Each card on the index page demonstrates a different interaction pattern and ships a copy-ready, portable CSS snippet.” Live index groups cards as All / Essential / AI Agents / Effects / Texts / Pro.","at":"2026-08-26T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"The same library is packaged as an agent skill plus a Refine companion (/refine.html; historically also npx transitions-refine live) tha","at":"2026-08-26T00:00:00.000Z"}],"interfaces":[{"kind":"skill"}],"origin":"seed","notes":[],"createdAt":"2026-08-26T00:00:00.000Z","updatedAt":"2026-08-26T00:00:00.000Z","stagingSeed":"leyline-0.3.0-staging","recordId":"cmp_transitions-dev","claims":{"name":"Transitions.dev","summary":"Site title Transitions.dev: UI transitions for AI agents. README: “an interactive collection of reusable CSS transitions. Each card on the index page demonstrates a different interaction pattern and ships a copy-ready, portable CSS snippet.” Live index groups cards as All / Essential / AI Agents / Effects / Texts / Pro.","kind":"resource","publisher":"","homepage":"https://transitions.dev/","repoUrl":"https://github.com/Jakubantalik/transitions.dev","costRange":"unknown","functions":["index"],"slices":[{"functionId":"index","label":"Index","note":"Site title Transitions.dev: UI transitions for AI agents. README: “an interactive collection of reusable CSS transitions. Each card on the index page demonstrates a different interaction pattern and ships a copy-ready, portable CSS snippet.” Live index groups cards as All / Essential / AI Agents / Effects / Texts / Pro.","cost":"unknown"}],"interfaces":[{"kind":"skill"}],"composabilityRationale":""},"relations":[],"signals":[],"claimVerification":[],"explain":{"score":3,"formula":"100 × sum(weight × value) over observed factors only. Unobserved factors are omitted, not zeroed.","factors":[{"id":"github_health","label":"GitHub health","weight":0.18,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"agent_use","label":"Agent use","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"human_notes","label":"Human notes","weight":0.14,"why":"insufficient evidence","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-26-transitions-dev.md\nSite title Transitions.dev: UI transitions for AI agents. README: “an interactive collection of reusable CSS transitions. Each card on the index page demonstrates a different interaction pattern and ships a copy-ready, portable CSS snippet.” Live index groups cards as All / Essential / AI Agents / Effects / Texts / Pro.","at":"2026-08-26T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"The same library is packaged as an agent skill plus a Refine companion (/refine.html; historically also npx transitions-refine live) tha","at":"2026-08-26T00:00:00.000Z"}],"evidence":"insufficient"},{"id":"composability","label":"Composability","weight":0.16,"why":"insufficient evidence","sources":[],"evidence":"insufficient"},{"id":"checklist","label":"Checklist","weight":0.1,"value":0,"contribution":0,"why":"No MCP surface is declared. No API is declared. Cost is unknown. 0 of 3 checklist fields are complete.","sources":[],"evidence":"observed"},{"id":"evidence_quality","label":"Evidence quality","weight":0.14,"value":0.22849520230941842,"contribution":0.031989328323318585,"why":"2 sources cover 1 evidence types. The latest dated evidence is 2026-08-26. Freshness is omitted unless observed as a signal.","sources":[{"kind":"human","label":"Compendium resource card","excerpt":"06 Knowledge Library/Resources/design/2026-08-26-transitions-dev.md\nSite title Transitions.dev: UI transitions for AI agents. README: “an interactive collection of reusable CSS transitions. Each card on the index page demonstrates a different interaction pattern and ships a copy-ready, portable CSS snippet.” Live index groups cards as All / Essential / AI Agents / Effects / Texts / Pro.","at":"2026-08-26T00:00:00.000Z"},{"kind":"human","label":"Compendium resource card","excerpt":"The same library is packaged as an agent skill plus a Refine companion (/refine.html; historically also npx transitions-refine live) tha","at":"2026-08-26T00:00:00.000Z"}],"evidence":"observed"},{"id":"benchmark","label":"Benchmarks","weight":0.12,"why":"insufficient evidence","sources":[],"evidence":"insufficient"}],"missing":["GitHub health: insufficient evidence","Agent use: insufficient evidence","Human notes: insufficient evidence","Composability: insufficient evidence","Benchmarks: insufficient evidence"]},"score":3}]}