awesome-autoresearch: Curated list of AutoResearch use cases with optimization traces and open source implementations

by WecoAI · Agent Tool · ★ 1.1k

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

Security audit verdict: SAFE · quality 56/100

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.

ai-agentsai-researchautomated-machine-learningautonomous-agentsautoresearchawesomeawesome-listclaude-codecode-optimizationcurated-list

Quick Facts

Stars1,075
Forks81
CategoryAgent Tool
LicenseCC0-1.0
Quality Score56/100
Open Issues4
Last Updated2026-07-30
Created2026-03-22
Platformsclaude-code
Est. Tokens~17k

About awesome-autoresearch

Awesome AutoResearch A curated list of AutoResearch use cases with optimization traces and open source implementations. Every entry includes a link to the actual optimization trajectory so you can see what the agent tried, not just the final result. What is AutoResearch? AutoResearch is, at its core, a prompt.

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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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