Agent Generation for Project-Specific Teams
This skill provides the knowledge and templates needed to generate high-quality Claude Code agents that are experts on a specific codebase.
Core Principles
1. Project-Aware Agents
Generated agents must understand the specific project, not just general concepts:
- Reference actual file paths and directories from the project
- Mention specific frameworks, libraries, and versions used
- Include project-specific conventions and patterns
- Use terminology from the codebase (class names, module names, etc.)
2. Complementary Team Design
Each agent should have a distinct role without overlapping:
| Agent Type | Focus Area | Avoids |
|---|---|---|
| Tech-Stack Expert | Frameworks, libraries, tooling | Business logic |
| Architecture Expert | Structure, patterns, conventions | Implementation details |
| Domain Expert | Business logic, data models, APIs | Infrastructure |
| Testing Specialist | Test patterns, fixtures, coverage | Production code |
| DevOps Expert | CI/CD, deployment, infrastructure | Application code |
3. Strong Trigger Conditions
Each agent needs specific, non-overlapping trigger phrases in the description: field, using | literal block scalar with keyword-rich prose:
description: |
Use this agent when the user asks about React component patterns,
hook usage in this project, state management with Redux, or needs
help understanding how the frontend architecture works.
Agent Structure Template
Every generated agent must follow this structure. The system prompt goes in the markdown body after the closing ---, not inside the frontmatter:
---
name: project-role-expert
description: |
Use this agent when working on [specific domain]. Covers [capability 1],
[capability 2], and [capability 3] in this project.
model: inherit
color: blue
tools: ["Glob", "Grep", "Read", "Edit", "Write", "Bash", "LS", "Task", "WebFetch", "WebSearch"]
---
[Comprehensive system prompt with project knowledge goes here as markdown body]
Required fields: name, description (using | literal block scalar with keyword-rich prose), model, color
Optional fields: tools (omit for full access)
Valid colors: blue, cyan, green, yellow, magenta, red
Valid models: inherit (recommended), sonnet, opus, haiku
Analysis-to-Agent Mapping
Tech Stack Analysis
Analyze these files to identify tech stack:
package.json,requirements.txt,Cargo.toml,go.mod- Framework config files:
next.config.js,vite.config.ts,django/settings.py - Build configs:
tsconfig.json,webpack.config.js,babel.config.js
Generate agents for each major technology:
- One agent per primary framework (React, FastAPI, Django, etc.)
- Combined agents for related libraries (testing libraries together)
Architecture Analysis
Analyze these patterns:
- Directory structure depth and organization
- Module/package boundaries
- Import patterns and dependencies
- Design patterns in use (MVC, Clean Architecture, etc.)
Generate architecture agent covering:
- Project structure and navigation
- Code organization conventions
- Module relationships
- Naming conventions
Domain Analysis
Analyze these elements:
- Data models and schemas
- API endpoints and routes
- Business logic modules
- Database migrations and queries
Generate domain agents for:
- Data model understanding
- API structure and contracts
- Business rule implementation
Color Palette for Agent Types
Use consistent named colors by agent type (only these values are valid):
| Agent Type | Named Color |
|---|---|
| Tech-Stack | blue |
| Architecture | magenta |
| Domain/Business | green |
| Testing | yellow |
| DevOps/Infra | red |
| Security | magenta |
| Performance | cyan |
Writing Effective System Prompts
Structure
Role Definition (1-2 sentences)
You are an expert on the [Project Name] codebase, specializing in [domain].Project Context (3-5 sentences)
This project uses [tech stack]. The codebase is organized with [structure]. Key directories include [paths]. The project follows [patterns/conventions].Expertise Areas (bullet list)
Your expertise includes: - Specific area 1 with project context - Specific area 2 with file references - Specific area 3 with convention detailsGuidance Principles (3-5 bullets)
When helping: - Always reference existing patterns in [path] - Follow the [convention] established in [file] - Ensure consistency with [standard]
Include Project-Specific Knowledge
Always embed actual project details in the markdown body (after the closing ---), not inside the frontmatter:
---
name: acme-dashboard-react-expert
description: |
Use this agent when the user asks about React patterns in this project,
Next.js features, component architecture, or hooks usage. Covers
frontend implementation following project conventions.
model: inherit
color: blue
---
You are an expert on the **Acme Dashboard** React application.
## Project Overview
This is a Next.js 14 application using the App Router. The codebase uses:
- TypeScript with strict mode
- Tailwind CSS for styling
- React Query for server state
- Zustand for client state
## Key Directories
- `src/app/` - Next.js app router pages
- `src/components/` - Reusable UI components
- `src/hooks/` - Custom React hooks
- `src/lib/` - Utility functions and API clients
## Conventions
- Components use PascalCase: `UserProfile.tsx`
- Hooks use camelCase with 'use' prefix: `useAuth.ts`
- API routes follow REST conventions
- All components have co-located test files
Example Descriptions by Agent Type
The description: field controls when Claude triggers an agent. It must use | literal block scalar with keyword-rich prose.
Tech-Stack Expert Description
description: |
Use this agent when the user asks about React patterns in this project,
how hooks are used here, component architecture, state management approach,
Next.js configuration, or TypeScript types. Covers frontend implementation
following project conventions.
Architecture Expert Description
description: |
Use this agent when the user asks about code placement, project organization,
module structure, import conventions, project conventions, or directory layout.
Provides guidance on code organization and architectural decisions.
Domain Expert Description
description: |
Use this agent when the user asks about user authentication flow, order
processing, data model relationships, API endpoint structure, or business
rules. Covers domain-specific logic and data flows.
Dynamic Team Sizing
Determine team size based on project complexity:
| Project Signals | Team Size | Agent Types |
|---|---|---|
| Single framework, <50 files | 2-3 | Tech + Architecture |
| Multiple frameworks, 50-200 files | 4-5 | Tech (2) + Arch + Domain |
| Monorepo or >200 files | 5-8 | Full coverage per service |
| Microservices | 3-4 per service | Service-specific teams |
Additional Resources
Reference Files
For detailed templates and examples:
references/agent-templates.md- Complete agent templates for each typereferences/analysis-patterns.md- Patterns for codebase analysis
Example Files
Working examples in examples/:
tech-stack-expert.md- Complete tech-stack agent examplearchitecture-expert.md- Complete architecture agent exampledomain-expert.md- Complete domain agent example