labrat: Autonomous multi-branch research lab. Branches compete for compute budget. The system converges on what works

by ProjectDXAI · Agent Tool · ★ 237

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

Security audit verdict: SAFE · quality 66/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentsautonomous-researchclaude-codeexperiment-managementmarket-allocationmulti-agentresearch-automation

Quick Facts

Stars237
Forks5
LanguagePython
CategoryAgent Tool
LicenseMIT
Quality Score66/100
Open Issues1
Last Updated2026-08-07
Created2026-03-30
Platformsclaude-code, python
Est. Tokens~114k

About labrat

labrat English | 简体中文 is a local-first runtime that puts Claude Code or Codex on a real research problem with a scoreboard and enough structure to run for hours. Population search, not single-thread: families of ideas compete for compute budget, and the ones that produce real signal earn more room to keep going.

Compatible Skills

These tools work well together with labrat for enhanced workflows:

labrat alternative? Top 6 similar tools

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  • af-deep-research by Agent-Field · ⭐ 98

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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