CrewAI engine for agentic-control - autonomous AI crews for development tasks
Project description
CrewAI - Package-Agnostic Crew Runner
A generic CrewAI engine that discovers and runs crews defined in packages' .crewai/ directories.
Quick Start
# List all packages with crews
just crew-list
# Run a specific crew
just crew-run otterfall game_builder --input "Create a QuestComponent"
# Show crew details
just crew-info otterfall game_builder
Architecture
Engine (internal/crewai)
The engine provides:
- Discovery: Finds
.crewai/directories in packages - Loading: Parses YAML configs into CrewAI objects
- Running: Executes crews with provided inputs
- CLI:
crewai run <package> <crew> --input "..."
Package Crews (packages/<name>/.crewai/)
Each package can define its own crews:
packages/otterfall/.crewai/
manifest.yaml # Package crew configuration
knowledge/ # Domain-specific knowledge files
crews/
game_builder/
agents.yaml # Agent definitions
tasks.yaml # Task definitions
CLI Usage
# From the internal/crewai directory
cd internal/crewai
# List available packages and crews
uv run python -m crew_agents list
# Run a crew
uv run python -m crew_agents run otterfall game_builder --input "Create X"
# Run with input from file
uv run python -m crew_agents run otterfall game_builder --file tasks.md
# Show crew info
uv run python -m crew_agents info otterfall game_builder
# Legacy: Direct build (uses otterfall game_builder)
uv run python -m crew_agents build "Create a QuestComponent"
Adding Crews to a Package
- Create
.crewai/manifest.yaml:
name: mypackage
description: My package crews
version: "1.0"
crews:
builder:
description: Build components
agents: crews/builder/agents.yaml
tasks: crews/builder/tasks.yaml
knowledge:
- knowledge/patterns
- Create agent and task YAML files:
# crews/builder/agents.yaml
senior_engineer:
role: Senior Engineer
goal: Write production-quality code
backstory: You are a senior developer...
# crews/builder/tasks.yaml
write_code:
description: Write the requested code
expected_output: Working code with tests
agent: senior_engineer
- Add knowledge files (optional):
knowledge/
patterns/
architecture.md
examples.ts
GitHub Actions
The CrewAI workflow can be triggered manually:
- Go to Actions → CrewAI Tasks
- Select package and crew
- Choose input type (Kiro tasks or custom)
- Run workflow
Development
# Install dependencies
cd internal/crewai
uv sync
# Run tests
uv run pytest
# Test tools
uv run python -m crew_agents test-tools
Dependencies
- crewai: Core CrewAI framework
- anthropic: Claude API access
- pyyaml: YAML parsing
- mesh-toolkit: 3D asset generation (optional, from mesh-toolkit PR)
Project details
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