AgentCompass: [EMNLP 2026] AgentCompass is an extensible open-source evaluation infrastructure for systematically assessing

by open-compass · Codex Skill · ★ 170

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How to install AgentCompass

git clone https://github.com/open-compass/AgentCompass.git && cd AgentCompass

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

Security audit verdict: SAFE · quality 69/100

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.

agentbenchmark-frameworkclaude-codecodexevaluation-frameworkharness

Quick Facts

Stars170
Forks37
LanguagePython
CategoryCodex Skill
LicenseApache-2.0
Quality Score69/100
Open Issues15
Last Updated2026-10-22
Created2025-09-04
Platformsclaude-code, codex, python
Est. Tokens~15k

About AgentCompass

English | Chinese ⭐ Star AgentCompass on GitHub and join us in building the next-generat

Compatible Skills

These tools work well together with AgentCompass for enhanced workflows:

  • WebCanvas — semantic(0.27)+complementary+rare_topics+same_lang+similar_pop+shared_platform (64%)
  • toolbench — semantic(0.37)+complementary+same_lang+similar_pop+shared_platform (63%)
  • coder_eval — semantic(0.24)+complementary+rare_topics+same_lang+similar_pop+shared_platform (63%)
  • moonshot — semantic(0.22)+complementary+rare_topics+same_lang+similar_pop+shared_platform (62%)

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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:

View on GitHub → Browse Codex Skill tools