kol-content-monitor
Track what key opinion leaders (KOLs) in your space are posting on LinkedIn and Twitter/X. Surfaces trending narratives, high-engagement topics, and early signals of emerging conversations before they peak. Chains linkedin-profile-post-scraper and twitter-mention-tracker. Use when a marketing team wants to ride trends rather than create them from scratch, or when a founder wants to know which topics are resonating with their audience.
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Low
Low-risk findings worth noting
Low
Low-risk findings.
2 low severity findings. 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
In Phase 1 and Phase 2 the workflow scrapes outsider-authored LinkedIn posts and Twitter/X tweets from user-specified KOL profile URLs/handles, then ingests their free-text content for filtering, topic extraction, and clustering.
W012: Unverifiable external dependency detected (runtime URL that controls agent).
What this means
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.
Why it was flagged
The LinkedIn profile URLs https://www.linkedin.com/in/lennyrachitsky/ and https://www.linkedin.com/in/kylepoyar/ are passed as runtime inputs to the linkedin-profile-post-scraper and the scraped posts are used as model input, meaning remote content from these URLs directly controls the agent's prompts/output.
- Repository
- gooseworks-ai/goose-skills
- Commit
8866b2a
- Audited
- Security analysis
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