recursive-improve: Make your agents recursively self-improve

by kayba-ai · Agent Tool · ★ 295

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How to install recursive-improve

uv tool install "recursive-improve[all] @ git+https://github.com/kayba-ai/recursive-improve.git"
uv add "recursive-improve @ git+https://github.com/kayba-ai/recursive-improve.git"

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 65/100

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. Full audit →

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.

agent-learningagentsaiai-agentai-toolsllmmachine-learning

Quick Facts

Stars295
Forks32
LanguagePython
CategoryAgent Tool
LicenseApache-2.0
Quality Score65/100
Open Issues4
Last Updated2026-03-31
Created2026-03-28
Platformspython
Est. Tokens~119k

About recursive-improve

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Compatible Skills

These tools work well together with recursive-improve for enhanced workflows:

  • superml — semantic(0.29)+complementary+same_lang+similar_pop+shared_platform (60%)
  • agent-builder — semantic(0.26)+complementary+same_lang+similar_pop+shared_platform (59%)
  • mcp-server — semantic(0.21)+complementary+same_lang+similar_pop+shared_platform (57%)

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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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