chat-learnings-extractorExtract structured learnings (lessons, decisions, patterns, dead ends) from AI conversation exports using a local Ollama model or any OpenAI-compatible API....
Install via ClawdBot CLI:
clawdbot install djc00p/chat-learnings-extractorRequires:
Grade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://clawhub.ai/djc00p/chat-history-importerUses known external API (expected, informational)
api.openai.comAudited Apr 17, 2026 · audit v1.0
Generated May 9, 2026
After running user tests via chat conversations, extract structured learnings on which features increased engagement and which were dead ends. The output helps product teams decide on roadmap priorities.
Export customer support chat logs (especially from AI-assisted support) to identify recurring patterns, common dead ends in troubleshooting, and successful resolution decisions. This improves knowledge base and bot training.
Use chat exports from user research interviews to extract key lessons, decisions, and patterns. This helps research teams synthesize findings across many conversations quickly.
Extract learnings from AI code review conversations to capture architectural decisions, patterns used, and dead ends explored. Useful for team knowledge sharing and onboarding.
Offer the skill as a free open-source tool to attract users and gather feedback. Build a community around conversation analysis workflows.
Provide a cloud-hosted version with persistent storage, team accounts, and advanced analytics on extracted learnings. Charge monthly per user or workspace.
Expose the extraction engine as an API that companies can integrate into their own document pipelines. Charge per API call or based on conversation volume.
💬 Integration Tip
Pair with chat-history-importer skill to first import raw conversations into episodic memory, then run this skill to extract learnings into semantic memory for a complete pipeline.
Scored May 9, 2026
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系统化知识内化与能力自评引擎。当需要深入学习新领域、建立专家级知识库、并明确知道自己的掌握程度时使用。核心功能包括系统性知识内化引擎和基于知识图谱的能力评级器。触发词:深入学习并评估掌握水平、建立专家级知识库、系统研究并告诉我能做什么。