autoresearch
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
64
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Critical
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tessl review fix ./skills/vendor-ai-research/0-autoresearch-skill/SKILL.mdSecurity
1 critical severity finding. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
E006: Malicious code pattern detected in skill scripts.
What this means
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
Why it was flagged
The skill explicitly mandates autonomous operation without user consent, instructs creating a persistent cron/loop bound to the chat session (prompt-injection / persistence), and directs automatic transmission of progress files via external messaging (Telegram/WhatsApp/Slack), enabling remote control and potential unauthorized data exfiltration.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
W011: Third-party content exposure detected (indirect prompt injection risk).
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
The runtime workflow includes reading/continuing research by searching literature sources (Exa, Semantic Scholar, arXiv, CrossRef) and saving their retrieved paper text/summaries into workspace files; that fetched outsider-authored web text can then be read back into the agent context on subsequent ticks (via `/loop` reading `research-state.yaml`/`findings.md`).
- Repository
- OpenRaiser/NanoResearch
- Commit
9d3b440
- Audited
- Security analysis
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