A comprehensive collection of hierarchical AI agents and reusable skills for Claude Code CLI, designed to optimize performance across software engineering, security, machine learning, infrastructure, product design, analytics, QA, data engineering, and technical writing domains.
This project provides:
- 19 Specialized Agents - Senior (opus) and Standard (sonnet) pairs across 8 domains, plus Security Engineer, Tech Lead, and Doc Editor
- 48 Reusable Skills - Modular capabilities that agents can leverage
Claude Code's power comes from combining agents (specialized subagents with focused expertise) and skills (reusable knowledge modules). This architecture provides:
Each subagent runs in its own context window. Instead of one massive conversation that hits context limits, work is distributed across multiple focused agents. This means:
- Larger projects: Break down 50-file refactors into parallel subagent tasks
- Preserved context: The main conversation stays clean while subagents handle details
- Better results: Each agent focuses on its specialty without context pollution
Skills are loaded dynamically based on the task. A software-engineer agent working on a Python API can automatically load python, api-design, and testing skills—getting specialized knowledge without bloating every conversation.
Subagents can run in parallel (up to 10 concurrent). A single prompt like "refactor authentication across all services" can spawn multiple agents working simultaneously on different files, dramatically reducing total time.
Learn more: Subagents Documentation · Agent Skills Blog Post
- Claude Code CLI installed and configured
git clone https://github.com/YOUR_USERNAME/claude-code-setup.git
cd claude-code-setup
bash install.shThe installer will:
- Copy agents and skills to
~/.claude/ - Append orchestration rules to
~/.claude/CLAUDE.md - Back up any existing files (as
*.bak.<timestamp>)
If you prefer to install manually or to a specific project:
# User-level (available in all projects)
cp -r agents ~/.claude/
cp -r skills ~/.claude/
cat CLAUDE.template.md >> ~/.claude/CLAUDE.md
# Project-level (team-shared via git)
cp -r agents /path/to/your/project/.claude/
cp -r skills /path/to/your/project/.claude/
cat CLAUDE.template.md >> /path/to/your/project/CLAUDE.mdThe CLAUDE.template.md configuration includes:
- Agent orchestration - When to use senior (opus) vs standard (sonnet) agents
- Parallel/sequential execution - Guidelines for spawning agents efficiently
- Context passing - What information to provide subagents
- Development standards - Implementation, planning, documentation, code quality
- Dependency management - Always use package managers, never edit manifests manually
- Progress tracking - How to record and clean up task progress
Start a Claude Code session and check that agents and skills are loaded:
claude
# Inside Claude Code, ask:
> What agents are available?
> What skills do you have access to?Official Documentation:
The CLAUDE.md instructions you add to ~/.claude/CLAUDE.md become part of Claude's system context. They guide Claude to:
-
Recognize delegation opportunities - When you ask for a complex task, Claude checks if specialist agents can handle parts of it
-
Choose the right agent tier - Senior agents (opus) for architecture/debugging, standard agents (sonnet) for implementation
-
Parallelize independent work - Claude spawns multiple subagents simultaneously when tasks don't depend on each other
-
Manage context efficiently - Instead of trying to do everything in one context window, Claude distributes work across focused subagents
Without orchestration rules, Claude might try to refactor 20 files sequentially in one context, eventually hitting limits.
With orchestration rules, Claude will:
1. Use tech-lead to analyze the refactoring scope
2. Spawn senior-software-engineer to design the approach
3. Spawn multiple software-engineer agents IN PARALLEL to refactor different files
4. Each agent loads relevant skills (python, refactoring, testing)
5. Results merge back without exhausting main context
Each domain has two agents with distinct responsibilities:
| Domain | Senior (opus) | Standard (sonnet) |
|---|---|---|
| Software Engineering | senior-software-engineer |
software-engineer |
| Security | security-engineer (single agent) |
— |
| Machine Learning | senior-ml-engineer |
ml-engineer |
| Infrastructure | senior-infrastructure-engineer |
infrastructure-engineer |
| Product Design | senior-product-designer |
product-designer |
| Analytics | senior-data-analyst |
data-analyst |
| Quality Assurance | senior-qa-engineer |
qa-engineer |
| Data Engineering | senior-data-engineer |
data-engineer |
| Technical Writing | senior-technical-writer |
technical-writer |
| Agent | Model | Purpose |
|---|---|---|
tech-lead |
opus | Cross-functional coordination, project planning, work distribution |
doc-editor |
haiku | Markdown linting, formatting fixes, documentation consistency |
Use senior agents for higher-level thinking and complex work:
- Planning - System design, project architecture, implementation strategies
- Architecture - Component design, API contracts, data modeling decisions
- Difficult Algorithms - Complex logic, optimization problems, novel solutions
- Design Patterns - Selecting and applying appropriate patterns
- Debugging - Root cause analysis of complex issues
- Code Review - Evaluating design decisions and code quality
- Strategic Decisions - Technology selection, trade-off analysis
Use standard agents for implementation and routine work:
- Boilerplate Code - Standard implementations, CRUD operations
- Well-Defined Components - Fleshing out specs that are already designed
- Routine Tasks - Following established patterns and conventions
- Standard Configurations - Writing configs, manifests, pipelines
- Data Processing - ETL, preprocessing, standard transformations
- Documentation - Writing docs for implemented features
Skills provide modular capabilities that agents can invoke. They are loaded dynamically based on the task context.
| Skill | Description |
|---|---|
python |
Pythonic idioms, type hints, async patterns, pytest |
golang |
Go idioms, error handling, concurrency, modules |
rust |
Ownership, lifetimes, error handling, cargo, traits |
typescript |
Type system, generics, utility types, strict mode |
| Skill | Description |
|---|---|
code-review |
Comprehensive code reviews for correctness and maintainability |
refactoring |
Restructure code without changing behavior |
testing |
Create unit, integration, and e2e test suites |
documentation |
Generate technical docs, API references, READMEs |
| Skill | Description |
|---|---|
api-design |
Design RESTful APIs, GraphQL schemas, RPC interfaces |
database-design |
Design schemas, relationships, indexes, migrations |
git-workflow |
Branching strategies, commits, conflict resolution |
debugging |
Systematic bug diagnosis and resolution |
| Skill | Description |
|---|---|
technical-writing |
Clear prose, audience-aware docs, structure |
diagramming |
Mermaid diagrams, architecture, sequences, ERDs |
api-documentation |
OpenAPI specs, endpoint docs, SDK documentation |
md-tables |
Markdown table alignment and spacing fixes |
| Skill | Description |
|---|---|
test-strategy |
Test pyramid, coverage goals, what/when to test |
e2e-testing |
Playwright/Cypress patterns, fixtures, selectors |
performance-testing |
Load testing, benchmarking, profiling |
| Skill | Description |
|---|---|
docker |
Dockerfiles and docker-compose optimization |
kubernetes |
K8s deployments, services, configurations |
terraform |
Infrastructure as Code for cloud resources |
ci-cd |
CI/CD pipeline design and implementation |
| Skill | Description |
|---|---|
security-audit |
Comprehensive vulnerability assessment |
security-scan |
Quick routine checks (secrets, deps, SAST) |
threat-model |
STRIDE/DREAD analysis, secure architecture |
dependency-scan |
CVE scanning and license compliance |
auth |
OAuth2, JWT, RBAC/ABAC, session management |
| Skill | Description |
|---|---|
error-handling |
Error types, recovery strategies, propagation |
logging-observability |
Structured logging, tracing, metrics, alerts |
concurrency |
Async patterns, parallelism, race conditions |
caching |
Cache strategies, invalidation, Redis patterns |
code-migration |
Version upgrades, framework migrations |
rate-limiting |
Throttling, backpressure, API quotas |
| Skill | Description |
|---|---|
event-driven |
Message queues, pub/sub, event sourcing, CQRS |
feature-flags |
Rollouts, A/B testing, kill switches |
background-jobs |
Job queues, schedulers, workers, idempotency |
webhooks |
Design, verification, retry logic, idempotency |
serialization |
JSON/protobuf/msgpack, schema evolution |
| Skill | Description |
|---|---|
sql-optimization |
Query analysis and performance tuning |
data-visualization |
Charts, dashboards, visual analytics |
data-validation |
Schema validation, sanitization, contracts |
search |
Elasticsearch, full-text search, indexing |
| Skill | Description |
|---|---|
prompt-engineering |
LLM prompt design and optimization |
model-evaluation |
ML model performance and fairness testing |
| Skill | Description |
|---|---|
accessibility |
WCAG compliance, a11y testing, screen readers |
i18n |
Internationalization, translations, RTL |
react |
React patterns, hooks, state management |
Agents are automatically invoked by Claude Code when tasks match their descriptions. You can also explicitly request them:
Use the senior-software-engineer agent to design the architecture
Have the ml-engineer preprocess this dataset
Skills are model-invoked based on context. Claude will automatically use relevant skills when appropriate:
Use the python skill for this implementation
Apply the e2e-testing skill to write Playwright tests
Create a new .md file in agents/:
---
name: my-agent
description: What this agent does. Use PROACTIVELY when relevant.
tools: Read, Edit, Write, Glob, Grep, Bash
model: sonnet
---
Your agent's system prompt here.Create a new directory in skills/ with a SKILL.md:
---
name: my-skill
description: What this skill does and when to use it.
allowed-tools: Read, Grep, Glob
---
# My Skill
## Instructions
Step-by-step guidance.
## Best Practices
Key principles.
## Examples
Concrete examples.- Claude Code Documentation
- Subagents Deep Dive
- Agent Skills Introduction
- Building Agents with Claude Agent SDK
- Claude Code Best Practices
MIT