Where does the skill store my captured insights?

The skill routes data based on scope: workflow-level insights go to the root CLAUDE.md, while code-specific pitfalls are added to the relevant AGENTS.md file in that directory.

Can I review the AI's findings before they are saved?

Yes, the skill presents every potential learning to the user for confirmation, allowing you to accept, edit, or reject candidates before they are written to disk.

What is the Intent Layer Compound skill?

It is a specialized utility for Claude Code that scans your interaction history to identify, extract, and document technical learnings, pitfalls, and patterns into your project files.

How does it handle duplicate information?

It includes a deduplication mechanism that analyzes existing content; if a similar learning already exists, the skill will skip it to keep your documentation clean.

When is the best time to use this skill?

You should run /intent-layer-compound after completing a feature, fixing a complex bug, or at the end of any significant coding session.

Intent Layer Learning Compound

Name: Intent Layer Learning Compound
Author: orban

byorban

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Aprendizaje y Documentación

Captures and triages developer insights, pitfalls, and patterns at the end of work sessions to automate project documentation.

The Intent Layer Compound skill streamlines the post-development workflow by analyzing AI conversations for undocumented insights and technical 'gotchas.' It automatically surfaces potential learnings—such as API quirks, architectural discoveries, and missing validation checks—and routes them to either global or local documentation files. By integrating directly into the Intent Layer framework, it ensures that valuable knowledge gained during a coding session is preserved for future sessions, preventing repeated mistakes and maintaining long-term project context without manual writing overhead.

Características Principales

01Structured triage prompts to manually capture missed insights and specific technical checks.

02Automatic deduplication to ensure documentation remains concise and free of redundant entries.

03Intelligent scope routing between global (CLAUDE.md) and directory-level (AGENTS.md) documentation.

043 GitHub stars

05Automated AI conversation scanning to identify corrections, discoveries, and patterns.

06Direct integration with learn.sh scripts for seamless writing to the Intent Layer.

Casos de Uso

01Conducting an end-of-day knowledge sync to ensure the AI's future context is updated with recent progress.

02Documenting architectural discoveries and build-system workarounds during a debugging session.

03Capturing undocumented API behaviors or edge cases after finishing a feature implementation.

Características Principales

01Structured triage prompts to manually capture missed insights and specific technical checks.

02Automatic deduplication to ensure documentation remains concise and free of redundant entries.

03Intelligent scope routing between global (CLAUDE.md) and directory-level (AGENTS.md) documentation.

043 GitHub stars

05Automated AI conversation scanning to identify corrections, discoveries, and patterns.

06Direct integration with learn.sh scripts for seamless writing to the Intent Layer.

Casos de Uso

01Conducting an end-of-day knowledge sync to ensure the AI's future context is updated with recent progress.

02Documenting architectural discoveries and build-system workarounds during a debugging session.

03Capturing undocumented API behaviors or edge cases after finishing a feature implementation.