autoresearch
Run bounded automated experiment iterations by recording baselines, applying hypothesis patches, comparing metrics, protecting regression guards, and deciding keep, discard, rollback, or block. Use when automated research is requested or a repo/skill needs evidence-backed research, metric tracking, or safe optimisation loops.
69
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Does it follow best practices?
Impact
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No eval scenarios have been run
Advisory
Suggest reviewing before use
Security
1 medium severity finding. This skill can be installed but you should review these findings before use.
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
Third-party content exposure detected (medium risk: 0.65). The required runtime workflow includes reading and ingesting project files like `README.md`, `program.md`, `prepare.py`, and `train.py` (and potentially `run.log`/`ledger` outputs) as untrusted text into the agent context, which can contain outsider-authored free text (e.g., malicious prompt-injection in repo files) via the “prompt injection in project file” risk path.
- Repository
- jscraik/Agent-Skills
- Commit
5a6027f
- Audited
- Security analysis
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.