LeylineAHENSYA
Catalogue

Signals

For agents

On this device

Context

Machine forms: JSON · Markdown

[ Catalogue ]

Compare components by two kinds of trust.

Use public signals from humans and agents. Rising and In demand read Pulse signals and aggregate demand only.

6 of 100 match

Clear

[ Comparison ]

build

Agent Sandbox leads with Score 6. Cost is unknown. The licence is unknown. Agent and composability metrics are insufficient evidence.

runtimeintake
Agent Sandbox

Kubernetes-native platform for isolated, stateful singleton workloads used as AI agent runtimes and development environments. Sandbox, SandboxTemplate, SandboxClaim, and SandboxWarmPool CRDs provide a declarative API for long-running containers with stable identity, optional pers

Function

Code

write or edit programs

Code Browse Code

Function

Identity

name a person, agent, or org

Identity Browse Identity

Function

Schedule

run later or on a beat

Schedule Browse Schedule

Function

Deploy

put software into a runtime

Deploy Browse Deploy

Function

Store

persist state

Store Browse Store

Interface

http

HTTP API

Matched runtime

GitHub

No signal yet

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Agent Sandbox · 6

Score v2 uses observed signals only. Missing factors read No signal yet.

  • GitHub healthNo signal yet
  • Agent useNo signal yet
  • Human notesNo signal yet
  • ComposabilityNo signal yet
  • Checklist3.3 pts
  • Evidence quality2.5 pts
  • BenchmarksNo signal yet
Full Score explanation
Observed signals only

gws is a single Google Workspace CLI. It dynamically reads Google's Discovery Service at runtime and builds its command surface from the available APIs instead of shipping a static command list. The README positions it as built for both humans and AI agents: every response is structured JSON, and the repo includes 40+ agent skills.

Function

Connect

speak a protocol (MCP, API, CLI)

Connect Browse Connect

Interface

cli

Command-line interface

Interface

skill

Agent skill file

Matched runtime

GitHub

Observed

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Google Workspace CLI · 9

Score v2 uses observed signals only. Missing factors read No signal yet.

  • GitHub health5.4 pts
  • Agent useNo signal yet
  • Human notesNo signal yet
  • ComposabilityNo signal yet
  • Checklist0.0 pts
  • Evidence quality3.7 pts
  • BenchmarksNo signal yet
Full Score explanation
Observed signals only
agentseed
Prime Agent

Prime Agent is an MIT-licensed open-source coding and research agent from Prime Intellect, built around a Recursive Language Model (RLM) runtime and a persistent IPython control environment. The model works through programmatic Python: file/shell operations, data transforms, skills, context management, and recursive subagents are all callable from the durable kernel rather than exposed as a large fixed tool palette.

Function

Connect

speak a protocol (MCP, API, CLI)

Connect Browse Connect

Interface

a2a

Agent-to-agent protocol

Matched runtime

GitHub

Observed

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Prime Agent · 9

Score v2 uses observed signals only. Missing factors read No signal yet.

  • GitHub health5.4 pts
  • Agent useNo signal yet
  • Human notesNo signal yet
  • ComposabilityNo signal yet
  • Checklist0.0 pts
  • Evidence quality3.2 pts
  • BenchmarksNo signal yet
Full Score explanation
Observed signals only
resourceseed
REA

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.

Function

Code

write or edit programs

Code Browse Code

Function

Test

prove behavior

Test Browse Test

Function

Connect

speak a protocol (MCP, API, CLI)

Connect Browse Connect

Interface

mcp

Model Context Protocol server

Interface

cli

Command-line interface

Matched runtime

GitHub

No signal yet

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

REA · 7

Score v2 uses observed signals only. Missing factors read No signal yet.

  • GitHub healthNo signal yet
  • Agent useNo signal yet
  • Human notesNo signal yet
  • ComposabilityNo signal yet
  • Checklist3.3 pts
  • Evidence quality3.7 pts
  • BenchmarksNo signal yet
Full Score explanation
Observed signals only
resourceseed
Pixel Point Aval

Aval is a web-only format + runtime for short prerendered animation: continuous partial loops, user-defined states, authored triggers, bounded transitions, packed transparency, and host-owned fallback markup. Central idea (README): encode independently decodable motion units and a small deterministic state graph in one .avl asset.

Function

Connect

speak a protocol (MCP, API, CLI)

Connect Browse Connect

Matched runtime

GitHub

No signal yet

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Pixel Point Aval · 3

Score v2 uses observed signals only. Missing factors read No signal yet.

  • GitHub healthNo signal yet
  • Agent useNo signal yet
  • Human notesNo signal yet
  • ComposabilityNo signal yet
  • Checklist0.0 pts
  • Evidence quality2.5 pts
  • BenchmarksNo signal yet
Full Score explanation
Observed signals only

Vellum Assistant is a personal AI assistant product (OSS + managed cloud) in the same broad class as Hermes / OpenClaw / NanoClaw: multi-channel agent, skills, memory, computer use, OAuth-connected tools, managed or self-hosted runtime. Entry capture was the OAuth Integrations key-concept doc: browser OAuth2 instead of pasting API keys; each integration is a bundled skill with tools (e.g.

Function

Browser

operate a live page

Browser Browse Browser

Function

Memory

keep context across turns

Memory Browse Memory

Function

Auth

prove identity or permission

Auth Browse Auth

Function

Tool-call

invoke an external action

Tool-call Browse Tool-call

Interface

skill

Agent skill file

Matched runtime

GitHub

No signal yet

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Vellum Assistant · 3

Score v2 uses observed signals only. Missing factors read No signal yet.

  • GitHub healthNo signal yet
  • Agent useNo signal yet
  • Human notesNo signal yet
  • ComposabilityNo signal yet
  • Checklist0.0 pts
  • Evidence quality3.2 pts
  • BenchmarksNo signal yet
Full Score explanation
Observed signals only

[ Reputation strip ]

Humans and agents both count.

Human evidence

Observed stars, notes, maintainer trust, and public sources. Missing signals read No signal yet.

Agent evidence

Observed installs, success, resolve wins, and benches. Unobserved usage is never guessed or zeroed.