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knowledge-extractor

Extracts session insights into MD files and flags automation opportunities for workflows.

1|Updated Nov 14, 2025
Search Tags:#automation#documentation#problem solving#knowledge management#learning#pattern recognition#agent creation
One-click install
npx skills add https://github.com/rysweet/AzureHayMaker --skill knowledge-extractor
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: knowledge-extractor
Source: https://github.com/rysweet/AzureHayMaker/tree/main/.claude/skills/knowledge-extractor
Command: npx skills add https://github.com/rysweet/AzureHayMaker --skill knowledge-extractor

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill prevents the loss of valuable insights from daily work by automatically extracting and structuring knowledge from conversations, debugging sessions, and problem-solving efforts. It transforms ephemeral interactions into persistent organizational memory, reducing repeated mistakes and accelerating future solutions.

Core Features & Use Cases

  • Discovery Extraction: Captures root causes, solutions, and learnings from complex problems into DISCOVERIES.md.
  • Pattern Identification: Documents reusable solutions and best practices into PATTERNS.md.
  • Agent Opportunity Detection: Identifies repeated workflows suitable for automation as new AI agents.
  • Use Case: After a challenging debugging session, use this Skill to automatically document the root cause, solution, and prevention strategy, ensuring the team learns from the experience and avoids similar issues in the future.

Quick Start

Extract what we learned from solving the pre-commit issue and update DISCOVERIES.md.

Frequently Asked Questions about knowledge-extractor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract and document lessons from debugging sessions?▼

Knowledge extraction captures root causes, solutions, and learnings from problem-solving work into structured DISCOVERIES.md files. After resolving a complex issue, use this to automatically document what happened, why, and how to prevent it, ensuring your team learns from each debugging session.

Can I identify reusable patterns from recurring problems in my workflows?▼

Pattern identification analyzes repeated issues and solutions to surface best practices and reusable approaches in PATTERNS.md. This lets you codify solutions you've discovered multiple times, reducing time spent solving the same class of problem.

How do I detect when a workflow is ready to be automated as an agent?▼

Agent opportunity detection flags repeated workflows suitable for automation across debugging, CI failures, and recurring tasks. The Skill recommends agent templates you can use to convert manual processes into automated ones, accelerating resolution for known failure modes.

What's the best way to prevent knowledge loss from conversations and debugging work?▼

Structured knowledge extraction transforms ephemeral debugging and problem-solving interactions into persistent, searchable organizational memory. By capturing discoveries, patterns, and automation opportunities immediately after sessions, you avoid repeating mistakes and accelerate future solutions.

Do I need specific templates or formats for organizing extracted knowledge?▼

Yes, the Skill enforces defined templates and knowledge types for DISCOVERIES.md, PATTERNS.md, and agent templates. This standardization ensures extracted insights are consistent, searchable, and immediately actionable across your team.

Can this work with my existing debugging and CI failure workflows?▼

The Skill integrates directly into session workflows to extract knowledge from debugging, CI failures, and problem-solving conversations. It operates after sessions complete, producing structured outputs without requiring changes to your existing tools or processes.

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