Archon AI Coding Workflow Template
A simple yet reliable template for systematic AI-assisted development using create-plan and execute-plan workflows, powered by Archon - the open-source AI coding command center. Build on top of this and create your own AI coding workflows!
What is This?
This is a reusable workflow template that brings structure and reliability to AI coding assistants. Instead of ad-hoc prompting, you get:
- Systematic planning from requirements to implementation
- Knowledge-augmented development via Archon's RAG capabilities
- Task management integration for progress tracking
- Specialized subagents for analysis and validation
- Codebase consistency through pattern analysis
Works with Claude Code, Cursor, Windsurf, Codex, and any AI coding assistant that supports custom commands or prompt templates.
Core Workflows
1. Create Plan (/create-plan)
Transform requirements into actionable implementation plans through systematic research and analysis.
What it does:
- Reads your requirements document
- Searches Archon's knowledge base for best practices and patterns
- Analyzes your codebase using the
codebase-analystsubagent - Produces a comprehensive implementation plan (PRP) with:
- Task breakdown with dependencies and effort estimates
- Technical architecture and integration points
- Code references and patterns to follow
- Testing strategy and success criteria
Usage:
/create-plan requirements/my-feature.md
2. Execute Plan (/execute-plan)
Execute implementation plans with integrated Archon task management and validation.
What it does:
- Reads your implementation plan
- Creates an Archon project and tasks automatically
- Implements each task systematically (
todo→doing→review→done) - Validates with the
validatorsubagent to create unit tests - Tracks progress throughout with full visibility
Usage:
/execute-plan PRPs/my-feature.md
Why Archon?
Archon is an open-source AI coding OS that provides:
- Knowledge Base: RAG-powered search across documentation, PDFs, and crawled websites
- Task Management: Hierarchical projects with AI-assisted task creation and tracking
- Smart Search: Hybrid search with contextual embeddings and reranking
- Multi-Agent Support: Connect multiple AI assistants to shared context
- Model Context Protocol: Standard MCP server for seamless integration
Think of it as the command center that keeps your AI coding assistant informed and organized.
What's Included
.claude/
├── commands/
│ ├── create-plan.md # Requirements → Implementation plan
│ ├── execute-plan.md # Plan → Tracked implementation
│ └── primer.md # Project context loader
├── agents/
│ ├── codebase-analyst.md # Pattern analysis specialist
│ └── validator.md # Testing specialist
└── CLAUDE.md # Archon-first workflow rules
Setup Instructions
For Claude Code
-
Copy the template to your project:
cp -r use-cases/archon-example-workflow/.claude /path/to/your-project/ -
Install Archon MCP server (if not already installed):
- Follow instructions at github.com/coleam00/Archon
- Configure in your Claude Code settings
-
Start using workflows:
# In Claude Code /create-plan requirements/your-feature.md # Review the generated plan, then: /execute-plan PRPs/your-feature.md
For Other AI Assistants
The workflows are just markdown prompt templates - adapt them to your tool - examples:
Cursor / Windsurf
- Copy files to
.cursor/or.windsurf/directory - Use as custom commands or rules files
- Manually invoke workflows by copying prompt content
Cline / Aider / Continue.dev
- Save workflows as prompt templates
- Reference them in your session context
- Adapt the MCP tool calls to your tool's API
Generic Usage
Even without tool-specific integrations:
- Read
create-plan.mdand follow its steps manually - Use Archon's web UI for task management if MCP isn't available
- Adapt the workflow structure to your assistant's capabilities
Workflow in Action
New Project Example
# 1. Write requirements
echo "Build a REST API for user authentication" > requirements/auth-api.md
# 2. Create plan
/create-plan requirements/auth-api.md
# → AI searches Archon knowledge base for JWT best practices
# → AI analyzes your codebase patterns
# → Generates PRPs/auth-api.md with 12 tasks
# 3. Execute plan
/execute-plan PRPs/auth-api.md
# → Creates Archon project "Authentication API"
# → Creates 12 tasks in Archon
# → Implements task-by-task with status tracking
# → Runs validator subagent for unit tests
# → Marks tasks done as they complete
Existing Project Example
# 1. Create feature requirements
# 2. Run create-plan (it analyzes existing codebase)
/create-plan requirements/new-feature.md
# → Discovers existing patterns from your code
# → Suggests integration points
# → Follows your project's conventions
# 3. Execute with existing Archon project
# Edit execute-plan.md to reference project ID or let it create new one
/execute-plan PRPs/new-feature.md
Key Benefits
For New Projects
- Pattern establishment: AI learns and documents your conventions
- Structured foundation: Plans prevent scope creep and missed requirements
- Knowledge integration: Leverage best practices from day one
For Existing Projects
- Convention adherence: Codebase analysis ensures consistency
- Incremental enhancement: Add features that fit naturally
- Context retention: Archon keeps project history and patterns
Customization
Adapt the Workflows
Edit the markdown files to match your needs - examples:
- Change task granularity in
create-plan.md(Step 3.1) - Add custom validation in
execute-plan.md(Step 6) - Modify report format in either workflow
- Add your own subagents for specialized tasks
Extend with Subagents
Create new specialized agents in .claude/agents/:
---
name: "security-auditor"
description: "Reviews code for security vulnerabilities"
tools: Read, Grep, Bash
---
You are a security specialist who reviews code for...
Then reference in your workflows.