Proactive Bleeding-Edge research loop using a strict 3-step abstraction protocol to extract engine-category friction points without importing framework-category bias or stealing code. Triggers: Use this skill when executing periodic "horizon scans" for the Dream Pipeline, researching external solutions to deeply complex engine-level friction points, or evaluating JS ecosystem trends.
66
78%
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
Fix and improve this skill with Tessl
tessl review fix ./.agents/skills/industry-friction-radar/SKILL.mdLow
Low-risk findings.
1 low severity finding. 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.
The required workflow explicitly uses the `search_web` tool in Step 1 (Trend Ingestion) to fetch “bleeding-edge” web developments from public runtime web sources, which can introduce outsider-authored free text into the agent’s context during browsing/search.
c1ce853
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.