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.
66
80%
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
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.
In `scripts/multi_source_paper_explore.py`, the required runtime workflow performs multi-lane public paper/API discovery (e.g., OpenReview notes and works) by issuing HTTP requests based on user queries and then ingests returned titles/abstracts/metadata into the pipeline.
a7d9500
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.