Evidence-to-Skill acts as a trust filter that verifies unreliable online information before allowing AI agents to execute actions based on it.
2 upvotes
Tracked by Kanon since Aug 1, 2026
🤖 Agent teardown · skill
Job to be doneTo ensure AI agents only act on information from untrusted sources after it has been validated.
Who it is forAI developers and teams building autonomous agents that rely on real-time web data.
Prerequisitesopen source
Integrationsclaude-code
Pricing$0 (open source) + optional enterprise support
Traction · why it is risingGrowing adoption in open-source agent frameworks due to its role in reducing hallucination risks during tool use.
Why it matters
It addresses a critical reliability gap in AI agents by enforcing evidence-based action execution, making it essential for trustworthy automation.
Signal source: Show HN
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