reader-comments-analyzer

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Reads a batch of reader comments and produces a structured summary of recurring themes, unanswered questions, emotional tone, and actionable editorial signals — so editors and journalists can understand what their audience actually took from a piece.

AI & Automation 16 stars 0 forks Updated yesterday MIT

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Skill Content

# Reader Comments Analyzer ## What This Skill Does Reads a batch of reader comments and produces a structured summary of recurring themes, unanswered questions, emotional tone, and actionable editorial signals — so editors and journalists can understand what their audience actually took from a piece. ## When To Use This Skill - After publishing a story that generated significant reader response and you want to understand what landed and what did not - When deciding whether to follow up on a story based on what readers are asking - When a piece attracted hostile or polarised comments and you need to understand the pattern before responding - When commissioning a follow-up or correction and you want to prioritise the issues readers flagged most often - When an editor wants an audience intelligence report without reading hundreds of individual comments ## What You Need To Provide **Required:** - A batch of reader comments (paste them directly — a minimum of 10 is useful; 30 or more gives more reliable patterns) - The headline or a one-sentence description of the original article (so the assistant can assess relevance and gap between article intent and reader response) **Optional:** - The platform the comments came from (website, YouTube, Facebook, Reddit, etc.) — tone and conventions differ by platform - Any specific question you want answered (e.g., "What are readers most angry about?" or "What follow-up story ideas are hidden in these comments?") - Whether you want the ana...

Details

Author
ur-grue
Repository
ur-grue/autopunk-media-skills
Created
4 months ago
Last Updated
yesterday
Language
Python
License
MIT

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