Searching internet for technical documentation using llms.txt standard, GitHub repositories via Repomix, and parallel exploration. Use when user needs: (1) Latest documentation for libraries/frameworks, (2) Documentation in llms.txt format, (3) GitHub repository analysis, (4) Documentation without direct llms.txt support, (5) Multiple documentation sources in parallel
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Low
Low-risk findings worth noting
Low
Low-risk findings.
2 low severity findings. Worth noting, but not necessarily harmful.
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.
Phase 2/3/4 require fetching and extracting arbitrary external documentation text at runtime (e.g., WebFetch of `llms.txt` and subsequent Explorer/Researcher reads of fetched URLs or cloned repository docs), which is outsider-authored free text that can be included in the agent’s LLM context.
The skill fetches instructions or code from an external URL at runtime, and the fetched content directly controls the agent’s prompts or executes code. This dynamic dependency allows the external source to modify the agent’s behavior without any changes to the skill itself.
The skill explicitly WebFetches llms.txt files from context7.com (e.g., https://context7.com/vercel/next.js/llms.txt) at runtime to drive which documents/agents to launch, and it also instructs cloning GitHub repos (e.g., https://github.com/org/library-name) and running Repomix to ingest remote repository content that becomes the agent's context, so these external URLs are runtime dependencies that directly control agent behavior.
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