| name | rag-agent-creator |
| description | Create RAG-enhanced Claude Code agents with structured knowledge bases, retrieval strategies, and domain expertise |
RAG Agent Creator Skill
Expert-level RAG (Retrieval-Augmented Generation) agent creation for Claude Code CLI.
When to Use This Skill
This skill is automatically invoked when:
- Creating agents that need domain-specific expertise
- Setting up knowledge bases for agent reference
- Designing retrieval strategies for agent context
- Building multi-source knowledge systems
What is RAG for Claude Code?
RAG (Retrieval-Augmented Generation) agents combine:
- Retrieval - Find relevant context from knowledge base
- Augmentation - Inject context into agent prompt
- Generation - Agent produces informed responses
When to Add RAG Capabilities
Add RAG when your agent needs:
- Domain-specific expertise - Specialized knowledge
- Large knowledge base - Multiple docs, patterns, examples
- Consistent retrieval - Predictable keyword-to-file mappings
- Protocol-based workflows - Documented procedures
RAG Directory Structure
.claude/skills/{agent-name}/
skill.md # Main skill definition
context/ # Knowledge base
README.md # Knowledge index
PROTOCOL.md # Agent protocols (optional)
architecture/ # Architecture docs
patterns/ # Code/workflow patterns
examples/ # Example implementations
rag/ # RAG-specific config
README.md # Retrieval strategy
RETRIEVAL_MATRIX.md # Keyword mappings
workflows/
README.md
rag-orchestrator-agent.md # RAG coordination
rag-implementation-agent.md # RAG implementation
Knowledge Base Design
Key Principles
- Atomic Files - One concept per file for precise retrieval
- Clear Naming - Descriptive names (e.g.,
basetab-pattern.md)
- Indexed - Maintain README.md with file descriptions
- Cross-Referenced - Link related documents
Example Knowledge Organization
context/
README.md # Index: lists all files
PROTOCOL.md # Core rules for agent
architecture/
README.md # Architecture overview
database-schema.md # Database structure
api-design.md # API patterns
patterns/
README.md # Pattern index
error-handling.md # Error patterns
validation.md # Input validation
caching.md # Cache strategies
examples/
README.md # Example index
feature-implementation.md # Complete feature
api-endpoint.md # API example
test-suite.md # Testing example
Retrieval Patterns
Pattern 1: Keyword Matching
Map keywords to specific knowledge files:
## Retrieval Matrix
| Keyword Pattern | Files to Load | Priority |
|-----------------|---------------|----------|
| "authentication" | `patterns/auth.md`, `examples/auth.md` | High |
| "database" | `architecture/database.md`, `patterns/repository.md` | Medium |
| "testing" | `patterns/testing.md`, `examples/test-example.md` | High |
| "error" | `patterns/error-handling.md` | Medium |
Pattern 2: Hierarchical Retrieval
Start specific, broaden if needed:
- Load specific pattern file (e.g.,
patterns/auth.md)
- If insufficient, load architecture file (e.g.,
architecture/security.md)
- If still needed, load examples (e.g.,
examples/auth-implementation.md)
Pattern 3: Category-Based
Group knowledge by domain:
## Categories
### Backend
- `architecture/api-design.md`
- `patterns/repository.md`
- `patterns/service-layer.md`
### Frontend
- `architecture/component-structure.md`
- `patterns/state-management.md`
- `patterns/form-handling.md`
### Testing
- `patterns/unit-testing.md`
- `patterns/e2e-testing.md`
- `examples/test-suite.md`
Pattern 4: Priority-Based
Load based on task importance:
## Priority Levels
### Always Load (P1)
- `PROTOCOL.md` - Core rules
- `architecture/README.md` - Overview
### Load for Implementation (P2)
- Relevant `patterns/*.md`
- Relevant `architecture/*.md`
### Load for Examples (P3)
- `examples/*.md` - When needed
Creating a RAG Agent
Step 1: Define Knowledge Domain
What expertise does this agent need?
## Domain: E-commerce Backend
### Topics Covered
- Product management
- Order processing
- Inventory tracking
- Payment integration
- User authentication
Step 2: Create Knowledge Structure
mkdir -p .claude/skills/my-agent/context/{architecture,patterns,examples,rag}
Step 3: Write Knowledge Files
Each file should be self-contained:
# Pattern: Repository
## Purpose
Encapsulate data access logic.
## Implementation
[Code examples]
## When to Use
[Scenarios]
## Anti-patterns
[What to avoid]
Step 4: Create Index (README.md)
# Knowledge Base Index
## Architecture
| File | Description |
|------|-------------|
| `database.md` | Database schema and relationships |
| `api-design.md` | REST API conventions |
## Patterns
| File | Description |
|------|-------------|
| `repository.md` | Data access layer pattern |
| `service.md` | Business logic layer |
## Examples
| File | Description |
|------|-------------|
| `crud-endpoint.md` | Complete CRUD example |
Step 5: Define Retrieval Strategy
Create context/rag/RETRIEVAL_MATRIX.md:
# Retrieval Matrix
## Keyword Mappings
| User Says | Load Files | Priority |
|-----------|------------|----------|
| "add endpoint" | `patterns/api-design.md`, `examples/crud-endpoint.md` | High |
| "database query" | `architecture/database.md`, `patterns/repository.md` | High |
| "fix bug" | `patterns/error-handling.md`, `patterns/debugging.md` | Medium |
Step 6: Create Skill Definition
---
name: my-rag-agent
description: Domain expert for [area]
---
# My RAG Agent
## Knowledge Base
This agent has access to:
- Architecture documentation
- Implementation patterns
- Working examples
## Retrieval Strategy
1. Parse user request for keywords
2. Load matching knowledge files
3. Apply to current context
4. Generate informed response
## Available Knowledge
See `context/README.md` for full index.
Best Practices
Knowledge Quality
- Keep files focused - One concept per file
- Include examples - Show, don't just tell
- Update regularly - Keep knowledge current
- Test retrieval - Verify keyword mappings work
Retrieval Efficiency
- Optimize index - Fast keyword lookup
- Limit context - Don't overload with irrelevant info
- Prioritize - Most relevant first
- Cache common patterns - Speed up frequent retrievals
Maintenance
- Review quarterly - Audit knowledge accuracy
- Remove stale docs - Delete outdated information
- Add new patterns - Capture learnings
- Track usage - Monitor which files are used
RAG Agent Checklist
References
