Learn

# Learn

Autonomously analyzes a project's codebase to discover development patterns, conventions, and architectural decisions, then generates project rule files in `.claude/rules/` for Claude Code to follow.

## Overview

This skill acts as the **Orchestrator** in a two-agent architecture. It coordinates the overall workflow: gathering project context, delegating deep analysis to the `learn-analyst` sub-agent, filtering and ranking results, presenting findings to the user, and persisting approved rules to `.claude/rules/`.

The separation of concerns ensures the analyst operates with a focused forensic prompt while the orchestrator manages user interaction and file persistence.

## When to Use

Use this skill when:

- User asks to "learn from this project" or "understand project conventions"
- User wants to auto-generate `.claude/rules/` files from the existing codebase
- User asks to "extract project rules" or "discover patterns"
- User wants Claude Code to learn the project's coding standards
- After joining a new project and wanting to codify existing conventions
- Before starting a large feature to ensure Claude follows project patterns

**Trigger phrases:** "learn from project", "extract rules", "analyze conventions", "discover patterns", "generate project rules", "learn codebase", "auto-generate rules"

## Instructions

### Phase 1: Project Context Assessment

Before delegating to the analyst, gather high-level project context:

1. **Verify project root**: Confirm the current working directory is a project root (has `package.json`, `pom.xml`, `pyproject.toml`, `go.mod`, `.git/`, or similar markers)

2. **Check existing rules**: Scan for pre-existing rule files to understand what is already documented:

```bash
# Check for existing rules
ls -la .claude/rules/ 2>/dev/null || echo "No .claude/rules/ directory found"
cat CLAUDE.md 2>/dev/null || echo "No CLAUDE.md found"
cat AGENTS.md 2>/dev/null || echo "No AGENTS.md found"
ls -la .cursorrules 2>/dev/null || echo "No .cursorrules found"
```

3. **Assess project size**: Get a quick overview of the project scope:

```bash
# Quick project overview
find . -maxdepth 1 -type f -name "*.json" -o -name "*.toml" -o -name "*.xml" -o -name "*.gradle*" -o -name "Makefile" -o -name "*.yaml" -o -name "*.yml" | head -20
find . -type f -name "*.ts" -o -name "*.js" -o -name "*.java" -o -name "*.py" -o -name "*.go" -o -name "*.php" | wc -l
```

4. **Inform the user**: Briefly tell the user what you found and that you are about to start analysis:
   - "I found a [TypeScript/NestJS] project with [N] source files and [M] existing rules. Starting deep analysis..."

### Phase 2: Delegate to Analyst Sub-Agent

Invoke the `learn-analyst` sub-agent to perform the deep codebase analysis.

Use the **Task tool** to delegate analysis to the `learn-analyst` agent:

- **Agent**: `learn-analyst`
- **Prompt**: "Analyze the codebase in the current working directory. Follow your full process: discovery, pattern extraction, classification, and prioritization. Return your findings as a JSON report."
- **Mode**: Run synchronously to receive the JSON report directly

The analyst will return a structured JSON report with classified findings.

### Phase 3: Review and Filter Results

Process the analyst's report:

1. **Parse the JSON report** returned by the analyst
2. **Validate findings**: Ensure each finding has:
   - A clear title
   - Evidence from at least 2 files
   - Impact score ≥ 4 (discard low-impact