Guide

How to Work with DevCrew

The core of DevCrew is INSTRUCTIONS.md — it turns any AI into a dev team that follows a structured workflow. After initialization, there are three ways to invoke Skills:

1. Natural Language (Recommended)

Describe what you need in AI chat. The AI automatically follows the PDEVI workflow:

You: I need to add auth middleware to the API
AI:  [PdM] Creating change add-api-auth, mode: Standard …

Common natural language triggers:

What you say	Skill triggered
"Let's make a plan" / "I want to add a feature"	plan
"What's the status?" / "Show progress"	status
"Run a checkpoint" / "Audit this"	checkpoint
"Archive it" / "This one's done"	release

2. CLI (Terminal)

Run directly in the terminal:

crew plan add-auth -m standard    # Create a change plan
crew status                       # Check progress
crew checkpoint                   # Phase audit
crew release                      # Archive changes

3. MCP Server (AI Tool Calls)

Let AI call Skills directly via the Model Context Protocol.

VS Code (GitHub Copilot): Add to .vscode/settings.json:

{
  "mcp": {
    "servers": {
      "dev-crew": {
        "command": "crew-mcp"
      }
    }
  }
}

Cursor: Add to .cursor/mcp.json:

{
  "mcpServers": {
    "dev-crew": {
      "command": "crew-mcp"
    }
  }
}

Once configured, AI can directly call crew_plan, crew_status, and other tools.

Mix and match: Use natural language for daily collaboration, CLI for quick ops, MCP for autonomous AI tool calls.

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Three Work Modes

Mode	Flow	Best For
Standard	Plan → Design → Execute → Verify → Iterate	New features, refactoring
Express	Plan → Execute → Verify	Bug fixes
Prototype	Plan → Design → Execute	Quick prototyping

Skills

Skill	CLI	MCP Tool	Purpose
init	crew init	crew_init	Initialize workspace + agent memory files
plan	crew plan <name>	crew_plan	Create a change and start working
status	crew status	crew_status	Check current progress
checkpoint	crew checkpoint	crew_checkpoint	Phase audit + consistency check + memory sync
release	crew release	crew_release	Archive changes + consolidate memory
agents	crew agents	crew_agents	List available specialists

Natural language works too — "run a checkpoint" triggers the checkpoint skill

Built-in Team

Agent	Responsibility
PjM Project Manager	Task decomposition, agent coordination, progress tracking
PdM Product Manager	Requirements analysis, PRD import, acceptance criteria
Architect	Tech decisions, task decomposition, dependency analysis
Implementer	Code generation, refactoring, dependency management
Tester	Test execution, acceptance checks, coverage
Reviewer	Code review, security scanning, best practices

PjM assembles the team on demand, creating additional agents as needed — no manual assignment required.

Agent Memory

Each agent maintains a long-term memory file in dev-crew/memory/, accumulating project knowledge, patterns, and preferences across changes. Memory is consolidated on release and auto-loaded on new sessions — the team gets better the more you use it.