What problem does it solve? When multiple RSS reports cover the same event, editors struggle to separate confirmed facts from single-source claims, contradictions, and unverified information. This Skill turns clustered event reports into structured fact cards so editorial decisions rest on traceable evidence instead of gut feeling. ## Core Features & Use Cases - Fact Separation: Distinguishes confirmed facts, single-source increments, disagreements between sources, and unverified content for each event. - Content Classification: Classifies each event into one of four types (github_project, open_source_technology, open_source_trend, news_event) with confidence scores and source-cited evidence. - Strict JSON Output: Returns event cards with conclusion, background, timeline, angles, and classification evidence, with explicit needs_review status when evidence is insufficient. - Use Case: In a WeChat content pipeline, after clustering today's RSS hotspots into events, run this Skill to produce fact cards that editors review before selecting topics for article production. ## Quick Start Ask the AI to generate event fact cards from the clustered event reports, separating confirmed facts, source increments, disagreements, and unverified items with classification evidence.
