awesome-evals: A curated, non-BS library of the best resources for building and evaluating AI agents

by benchflow-ai · Agent Tool · ★ 1.0k

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

Security audit verdict: SAFE · quality 53/100

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-evaluationai-agentsawesomeawesome-listbenchmarksevalsllmllm-evaluationrl-environments

Quick Facts

Stars1,025
Forks147
CategoryAgent Tool
Quality Score53/100
Open Issues81
Last Updated2026-11-04
Created2026-06-24
Est. Tokens~28k

About awesome-evals

Awesome Agent Evals A curated, opinionated, non-BS library of the best resources for building and evaluating AI agents — papers, blog posts, talks, courses, tools, and benchmarks. Maintained by BenchFlow · "Environments are the new data." Most "awesome" lists are link dumps.

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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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