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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:

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)

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

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"

• Assess project size: Get a quick overview of the project scope:

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

• 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:

• Parse the JSON report returned by the analyst

• Validate findings: Ensure each finding has:

• A clear title

• Evidence from at least 2 files

• Impact score ≥ 4 (discard low-impact findings)

• Well-formed markdown content

• Deduplicate against existing rules: Compare each finding title and content against existing .claude/rules/ files. Skip findings that duplicate existing rules.

• Select top 3: From the remaining findings, select the top 3 by impact score. If fewer than 3 remain after filtering, present whatever is left.

• If zero findings remain: Inform the user that the project is already well-documented or no significant undocumented patterns were found.

Phase 4: Present to User

Present the filtered findings to the user in a clear, structured format:

I analyzed your codebase and found N patterns worth documenting as project rules:

1. [RULE] <Title> (Impact: X/10) <One-line explanation>

2. [RULE] <Title> (Impact: X/10) <One-line explanation>

3. [RULE] <Title> (Impact: X/10) <One-line explanation>

Then ask the user for confirmation using AskUserQuestion:

• Present choices: "Save all N rules", "Let me choose which ones to save", "Cancel — don't save anything"

• If the user wants to select individually, present each rule one by one with "Save / Skip" options

• Never save automatically — always require explicit user approval

Phase 5: Persist Approved Rules

For each approved rule:

• Ensure directory exists:

mkdir -p .claude/rules

Generate the file name: Use the finding's title field converted to kebab-case:

• Example: "API Response Envelope Convention" → api-response-envelope-convention.md

• Avoid generic names like rule-1.md or learned-pattern.md

Check for conflicts: Before writing, check if a file with the same name already exists:

• If it exists, present a diff to the user and ask whether to replace, merge, or skip

Write the rule file: Create the file in .claude/rules/ with the analyst's pre-formatted content

Confirm to user: After saving, list all created files:

✅ Rules saved successfully:

.claude/rules/api-response-envelope-convention.md .claude/rules/feature-based-module-organization.md .claude/rules/test-factory-pattern.md

These rules will be automatically applied by Claude Code in future sessions.

Best Practices

• Run early in a project: Use this skill when joining a new project to quickly codify conventions

• Review before saving: Always verify the generated rules make sense for your project

• Iterate: Run the skill periodically as the project evolves — new patterns may emerge

• Edit after saving: Generated rules are starting points; refine them to match your exact preferences

• Commit rules to git: .claude/rules/ files are project-specific and should be version-controlled so the whole team benefits

Constraints and Warnings

Critical Constraints

• Never save without confirmation: Always ask the user before writing any files

• Project-local only: Only write to .claude/rules/ in the current project directory, never to global paths

• Read-only analysis: The analyst sub-agent must not modify any project files

• Evidence-based: Every rule must be backed by concrete evidence from the codebase

• No hallucination: Do not invent patterns that are not actually present in the codebase

• Respect existing rules: Do not overwrite existing rules without explicit user approval

• Keep rules focused: Each rule file should address one specific convention or pattern

Limitations

• Large monorepos: Analysis may take longer on very large codebases. The analyst scans representative samples, not every file.

• Polyglot projects: In multi-language projects, rules are generated per-language. Ensure the rule title indicates the language scope.

• Existing rules conflict: If the project already has comprehensive .claude/rules/ , the skill may find few or no new patterns. This is expected.

• Dynamic patterns: Some patterns only emerge at runtime (e.g., middleware ordering). This skill focuses on static codebase analysis.

Examples

Example 1: Learning from a NestJS project

User request: "Learn from this project"

Phase 1 — Context assessment:

Found: TypeScript/NestJS project with 142 source files Existing rules: 0 files in .claude/rules/ Starting deep analysis...

Phase 4 — Presentation:

I analyzed your codebase and found 3 patterns worth documenting as project rules:

1. [RULE] Feature-Based Module Organization (Impact: 9/10) All modules follow src/modules/<feature>/ with controller, service, dto, entity subdirectories.

2. [RULE] DTO Validation Convention (Impact: 8/10) All DTOs use class-validator decorators and follow Create/Update naming pattern.

3. [RULE] Error Response Envelope (Impact: 7/10) All API errors return { statusCode, message, error } consistent envelope format.

Save all 3 rules? [Save all / Let me choose / Cancel]

Phase 5 — Persistence:

✅ Rules saved successfully:

.claude/rules/feature-based-module-organization.md .claude/rules/dto-validation-convention.md .claude/rules/error-response-envelope.md

These rules will be automatically applied by Claude Code in future sessions.

Example 2: Project with existing rules

User request: "Discover project patterns"

Phase 1 — Context assessment:

Found: Java/Spring Boot project with 87 source files Existing rules: 4 files in .claude/rules/ Starting deep analysis...

Phase 3 — After filtering:

The analyst found 6 patterns, but 4 overlap with your existing rules. After deduplication, 2 new patterns remain:

1. [RULE] Repository Method Naming (Impact: 7/10) All custom repository methods use findBy/existsBy/countBy prefix convention.

2. [RULE] Integration Test Database Strategy (Impact: 6/10) Integration tests use @Testcontainers with PostgreSQL and @Sql for fixtures.

Save these 2 rules? [Save all / Let me choose / Cancel]