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continuous-learning

Capture debugging insights into reusable skills with frontmatter metadata and approvals.

Updated Aug 27, 2026
Search Tags:#debugging#knowledge-management#continuous-learning#agent-learning#trajectory-logging#notes-integration
One-click install
npx skills add https://github.com/project-purupuru/world-purupuru --skill continuous-learning-project-purupuru
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: continuous-learning
Source: https://github.com/project-purupuru/world-purupuru/tree/main/.claude/skills/continuous-learning
Command: npx skills add https://github.com/project-purupuru/world-purupuru --skill continuous-learning-project-purupuru

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Continuous Learning Skill helps agents preserve non-obvious debugging insights as lasting, structured knowledge, preventing loss when sessions end.

Core Features & Use Cases

  • Captures insights and patterns from debugging sessions into reusable, queryable skills.
  • Integrates with trajectory logs and NOTES.md to trace and reuse learnings.
  • Supports cross-session reuse to accelerate future debugging and engineering tasks.

Quick Start

After completing a debugging session, run the retrospective workflow to surface learnings.

Frequently Asked Questions about continuous-learning

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

FAQPage Schema
How do I preserve debugging insights as reusable knowledge across sessions?▼

You can preserve debugging insights by capturing them as structured skills with frontmatter metadata. This approach transforms ephemeral discoveries into retrievable knowledge that persists across sessions and projects.

How does trajectory logging help with agent learning and debugging?▼

Trajectory logging traces debugging sessions to capture non-obvious patterns and insights. Combined with NOTES.md integration, it creates a governed extraction path that surfaces reusable learnings for future engineering tasks.

What is the best way to capture non-obvious debugging patterns into a queryable format?▼

The best way to capture debugging patterns is running a retrospective workflow after a session. This enforces a structured extraction path with gates and approvals, persisting insights as queryable skills with frontmatter metadata.

Can I reuse debugging learnings across different code bases and projects?▼

Yes, captured debugging insights are designed for cross-session reuse across different code bases and projects. The structured knowledge base accelerates future debugging by making past discoveries retrievable.

Do I need NOTES.md integration to extract reusable debugging insights?▼

NOTES.md integration is part of the structured workflow for tracing and reusing learnings. It works alongside trajectory logging to ensure debugging insights are properly captured and linked for future retrieval.

When should I run the retrospective workflow to surface debugging learnings?▼

You should run the retrospective workflow after completing a debugging session. This timing ensures that fresh non-obvious insights and patterns are captured before session context is lost.

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