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

# How to fix cold start latency in AI sandboxes: techniques and tradeoffs

Function

Code

write or edit programs

Code Browse Code

Function

Route

send work to the right tool

Route Browse Route

Function

Test

prove behavior

Test Browse Test

Function

Cache

reuse a prior result

Cache Browse Cache

Function

Compose

assemble other functions

Compose Browse Compose

Interface

http

HTTP API

GitHub

No signal yet

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Fix Cold Start Latency in AI Sandboxes: Techniques · 9

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
  • Checklist6.7 pts
  • Evidence quality2.5 pts
  • BenchmarksNo signal yet
Full Score explanation
Observed signals only
resourceseed
Magika

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).

Function

Test

prove behavior

Test Browse Test

Function

Route

send work to the right tool

Route Browse Route

Interface

cli

Command-line interface

GitHub

Observed

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Magika · 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
appseed
OpenRouter

OpenRouter is a unified large language model inference router and model marketplace: one OpenAI-compatible HTTP application programming interface across many underlying inference providers, with automatic fallbacks and cost-aware routing. The marketplace object is models and inference providers (tokens in → tokens out), not installable agent tools ranked by dual human-and-agent reputation.

Function

Route

send work to the right tool

Route Browse Route

Function

Tool-call

invoke an external action

Tool-call Browse Tool-call

Interface

http

HTTP API

GitHub

Observed

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

OpenRouter · 9

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

  • GitHub health2.7 pts
  • Agent useNo signal yet
  • Human notesNo signal yet
  • ComposabilityNo signal yet
  • Checklist3.3 pts
  • Evidence quality3.2 pts
  • BenchmarksNo signal yet
Full Score explanation
Observed signals only

Published 17th January 2026

Function

Code

write or edit programs

Code Browse Code

Function

Browser

operate a live page

Browser Browse Browser

Function

Memory

keep context across turns

Memory Browse Memory

Function

Stream

deliver tokens or events live

Stream Browse Stream

Function

Test

prove behavior

Test Browse Test

Interface

http

HTTP API

GitHub

No signal yet

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Best code execution sandbox for AI agents in 2026 · 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

MIT-licensed Node CLI + agent skill by Peter Yang. It opens a target HTML/Markdown file or localhost route in a local browser review UI. The reviewer can directly change text/basic formatting, resize images, delete elements, and attach comments to selected text or blocks.

Function

Browser

operate a live page

Browser Browse Browser

Function

Route

send work to the right tool

Route Browse Route

Interface

cli

Command-line interface

Interface

skill

Agent skill file

GitHub

Observed

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Human Review · 6

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

  • GitHub health2.7 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
appintake
Onyx

Open-source enterprise search and AI assistant that connects to internal knowledge sources, indexes them with source permissions, and supplies humans and agents with answers and context. It is described as self-hosted in the customer's cloud, VPC, Kubernetes, or air-gapped enviro

Function

Code

write or edit programs

Code Browse Code

Function

Index

make retrieval cheap

Index Browse Index

Function

Route

send work to the right tool

Route Browse Route

Function

Test

prove behavior

Test Browse Test

GitHub

No signal yet

Agent use

No signal yet

Reputation

Human and agent evidence, together.

Score factors

Onyx · 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

[ 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.