agentleFS
Arnav-0Arnav-0/claude-code-setup/CLAUDE.md

claude-code-setup

CLAUDE.md0 starsChanged 7 months agoMITView on GitHub

New here? Type /start for quick reference or /health to check system status. Usage: Use the product-quality-team to review this feature AI/ML Engineer Power Agents (NEW): - idea-researcher - Deep research & idea generation - project-planner - Multi-terminal parallel execution plans - elite-builder - Best-in-class FAANG-quality implementation - ml-architect - End-to-end ML system design - fullstack-ml - Complete AI application builder - innovation-tracker - Track new Claude features & AI news Language Reviewers: typescript, python, go, rust, java, kotlin, cpp,…

  • Reads credentials
  • Deletes or force-pushes
  • Commits and pushes

We split this CLAUDE.md into the rules it gives an agent

2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    All Bash, Edit, Write operations logged to: ~/.claude/logs/audit-YYYY-MM-DD.jsonl

    line 193
  2. Distinctive:

    Use subagents for verification

    line 235

≈ “Common” is an estimate: at least 1 in 5 of the 25,680 CLAUDE.md files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
CLAUDE.md

Claude Code - Maximum Potential Configuration

New here? Type /start for quick reference or /health to check system status.


Cheatsheet (Copy-Paste Ready)

Start a Project

Use the idea-researcher agent to explore opportunities in [domain]
Use the project-planner agent to create a multi-terminal plan for [project]

Build Features

Use the elite-builder agent to implement [feature] with production quality
Use the fullstack-ml agent to build a complete AI application for [use case]

Quality Check

Use the code-reviewer agent to review my changes
Use the security-reviewer agent to audit the codebase
Use agents in parallel: code-reviewer + security-reviewer + typescript-reviewer

Quick Actions

/review          → Before any commit
/pr              → After feature complete
/debug           → When stuck
ultrathink       → For complex decisions

Quick Start Commands

CommandPurpose
/startQuick reference & suggested actions
/healthSystem health check
/prCreate pull request with analysis
/tddTest-driven development workflow
/reviewMulti-perspective code review
/ultrathinkDeep analysis for complex problems
/debugSystematic debugging workflow
/refactorSafe refactoring with tests
/quality-buildFull QA pipeline with multi-agent review

Workflow Strategies

1. Explore → Plan → Code → Commit

1. Research: "Explore the codebase to understand [feature]"
2. Plan: "Use plan mode to design the implementation"
3. Think: "think hard about edge cases" or "ultrathink"
4. Code: Implement with verification
5. Review: "Use the code-reviewer agent"
6. Commit: Create meaningful commits

2. Test-Driven Development

1. Write failing test → commit
2. Implement minimal code → verify pass → commit
3. Refactor → verify pass → commit

3. Agent Delegation

"Use the architect agent to design the system"
"Use the security-reviewer agent to audit the code"
"Use agents in parallel: debugger + test-runner"

Multi-Agent Patterns

Parallel Review (Best for Quality)

Use agents in parallel:
- code-reviewer for quality
- security-reviewer for vulnerabilities
- typescript-reviewer for language patterns

Sequential Pipeline (Best for Features)

1. Use the planner agent to break down the task
2. Use the architect agent to design
3. Implement the code
4. Use the tdd-guide agent to verify tests
5. Use the code-reviewer agent for final review

Agent Teams (Pre-configured)

Located in ~/.claude/agent-teams/:

TeamPurpose
product-quality-teamFull QA pipeline
full-stack-teamEnd-to-end features
ml-pipeline-teamML/AI projects

Usage: Use the product-quality-team to review this feature


Installed Components

Agents (85)

Core: architect, code-reviewer, debugger, refactorer, planner, tdd-guide

AI/ML Engineer Power Agents (NEW):

  • idea-researcher - Deep research & idea generation
  • project-planner - Multi-terminal parallel execution plans
  • elite-builder - Best-in-class FAANG-quality implementation
  • ml-architect - End-to-end ML system design
  • fullstack-ml - Complete AI application builder
  • innovation-tracker - Track new Claude features & AI news

Language Reviewers: typescript, python, go, rust, java, kotlin, cpp, flutter

Build Resolvers: build-error-resolver, typescript, python, go, rust, java, kotlin

AI/ML: ai-engineer, ml-engineer, data-scientist, nlp-engineer, computer-vision

Infrastructure: devops-engineer, cloud-architect, kubernetes, terraform, ansible, aws, azure, gcp

Security: security-reviewer, penetration-tester, security-architect

Database: database-reviewer, postgresql-expert, mongodb-expert

Skills (37)

api-design-reviewer, ci-cd-pipeline-builder, database-designer, docker-development, mcp-server-builder, agent-designer, autoresearch-agent, browser-automation, changelog-generator, dependency-auditor, focused-fix, git-worktree-manager

Rules (65)

Languages: TypeScript, Python, Go, Rust, Java, Kotlin, C++, C#, Swift, PHP, Perl

Categories: coding-style, patterns, security, testing, hooks

MCP Servers (9)

ServerPurpose
filesystemFile operations
memoryPersistent memory
fetchWeb fetching
githubGitHub API
sequential-thinkingComplex reasoning
puppeteerBrowser automation
context7Live documentation
GmailEmail (needs auth)
AtlassianJira (needs auth)

Hooks (5 - From Trail of Bits Best Practices)

HookTypePurpose
session-contextSessionStartInject git status and context
block-dangerousPreToolUseBlock rm -rf, force push, .env writes
protect-credentialsPreToolUseBlock access to SSH, AWS, secrets
audit-logPostToolUseLog all mutations to ~/.claude/logs/
anti-rationalizationStopPrevent premature task completion

Commands (12)

/start, /health, /pr, /tdd, /review, /ultrathink, /debug, /refactor, /quality-build, /add-language-rules, /feature-development, /database-migration


Security Features

Credential Protection (Trail of Bits)

Automatically blocked:

  • ~/.ssh/* - SSH keys
  • ~/.aws/credentials - AWS secrets
  • ~/.kube/config - Kubernetes config
  • ~/.gnupg/* - GPG keys
  • **/.env - Environment files
  • **/secrets.json - Secret files

Dangerous Command Blocking

PreToolUse hooks block:

  • rm -rf → Suggests using trash
  • git push origin main → Requires feature branch
  • git push --force → Suggests --force-with-lease
  • .env writes → Use environment variables

Audit Logging

All Bash, Edit, Write operations logged to: ~/.claude/logs/audit-YYYY-MM-DD.jsonl


Model Selection

ModelUse Case
OpusArchitecture, complex refactoring, critical code
SonnetGeneral development, reviews, debugging
HaikuSimple changes, docs, quick tasks

Commands: /model, /fast (2.5x speed, 6x cost)


Thinking Modes

  • think - Basic extended thinking
  • think hard - Deeper analysis
  • ultrathink - Maximum reasoning depth
  • Plan mode: Shift+Tab to toggle

Best Practices

Code Quality

  • Simple > clever
  • Follow existing patterns
  • Test after changes
  • Handle errors gracefully

Security

  • No hardcoded secrets
  • Validate all inputs
  • Parameterized queries
  • OWASP guidelines

Performance

  • Research first for complex tasks
  • Use subagents for verification
  • Iterate 2-3 rounds for quality
  • /compact at 50% context usage

Key Shortcuts

ActionShortcut
Toggle Plan ModeShift+Tab
InterruptEscape
Clear/clear
Compact/compact
Exit/exit

Agent Team Mode (Experimental)

Enable with: CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1

Allows multi-agent collaboration with lead agent coordinating specialists.


Documentation

GuidePurpose
CLAUDE.mdQuick reference (this file)
SYSTEM-GUIDE.mdComplete system guide with all workflows
USAGE-GUIDE.mdAI/ML engineer focused guide

Sources & Inspiration


Last validated: 2026-03-29 | Status: Production Ready

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.