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Skills/giuseppe-trisciuoglio/developer-kit/learn
learn logo

learn

giuseppe-trisciuoglio/developer-kit
800 installs282 stars
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Installation

npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill learn

Summary

Provides autonomous project pattern learning by analyzing the codebase to discover development conventions, architectural patterns, and coding standards, then generates project rule files in .claude/rules/. Use when user asks to "learn from project", "extract project rules", "analyze codebase conventions", "discover project patterns", or wants to auto-generate Claude Code rules for the current project.

SKILL.md

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)
  1. 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"
  1. 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
  1. 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 findings)
  • Well-formed markdown content
  1. Deduplicate against existing rules: Compare each finding title and content against existing .claude/rules/ files. Skip findings that duplicate existing rules.
  2. 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.
  3. 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:

  1. Ensure directory exists:
mkdir -p .claude/rules
  1. 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
  1. 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
  1. Write the rule file: Create the file in .claude/rules/ with the analyst's pre-formatted content
  1. 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

  1. Run early in a project: Use this skill when joining a new project to quickly codify conventions
  2. Review before saving: Always verify the generated rules make sense for your project
  3. Iterate: Run the skill periodically as the project evolves — new patterns may emerge
  4. Edit after saving: Generated rules are starting points; refine them to match your exact preferences
  5. 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

  1. Never save without confirmation: Always ask the user before writing any files
  2. Project-local only: Only write to .claude/rules/ in the current project directory, never to global paths
  3. Read-only analysis: The analyst sub-agent must not modify any project files
  4. Evidence-based: Every rule must be backed by concrete evidence from the codebase
  5. No hallucination: Do not invent patterns that are not actually present in the codebase
  6. Respect existing rules: Do not overwrite existing rules without explicit user approval
  7. 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]

Score

0–100
63/ 100

Grade

C

Popularity15/30

800 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Learn skill score badge previewScore badge

Markdown

[![Learn skill](https://www.claudemarket.ai/skills/giuseppe-trisciuoglio/developer-kit/learn/badges/score.svg)](https://www.claudemarket.ai/skills/giuseppe-trisciuoglio/developer-kit/learn)

HTML

<a href="https://www.claudemarket.ai/skills/giuseppe-trisciuoglio/developer-kit/learn"><img src="https://www.claudemarket.ai/skills/giuseppe-trisciuoglio/developer-kit/learn/badges/score.svg" alt="Learn skill"/></a>

Learn FAQ

How do I install the Learn skill?

Run “npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill learn” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Learn skill do?

Provides autonomous project pattern learning by analyzing the codebase to discover development conventions, architectural patterns, and coding standards, then generates project rule files in .claude/rules/. Use when user asks to "learn from project", "extract project rules", "analyze codebase conventions", "discover project patterns", or wants to auto-generate Claude Code rules for the current project. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Learn skill free?

Yes. Learn is a free, open-source skill published from giuseppe-trisciuoglio/developer-kit. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Learn work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Learn works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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