research-material-scout
Use when the user asks Codex to research, find learning materials, process "素材：" links, "请你读" / "精读" a material, build a material radar, or use SenSight-like broad information retrieval for career learning and Agent infra tracking. Do not use the career/Agent-infra routing bias for user-directed `整理笔记` into a named note.
67
81%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Low
Low-risk findings worth noting
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
SKILL.md specifies that for active research it will run `scripts/multi_source_paper_explore.py`, which fetches outsider-authored public content via multiple public API endpoints (e.g., arXiv/OpenReview/OpenAlex/bioRxiv/medRxiv/ChemRxiv) and then returns that extracted free-text (titles/abstracts) into a JSON payload that Codex would place into the agent’s LLM context for summarization/ranking.
- Repository
- huangruiteng/CS-Notes
- Commit
a2e95c0
- 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.