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README.md

Python Agent Example

A simple Python script demonstrating how an AI agent can use bd to manage tasks.

Features

  • Finds ready work using bd ready --json
  • Claims tasks by updating status
  • Simulates discovering new issues during work
  • Links discovered issues with discovered-from dependency
  • Completes tasks and moves to the next one

Prerequisites

  • Python 3.7+
  • bd installed: go install github.com/steveyegge/beads/cmd/bd@latest
  • A beads database initialized: bd init

Usage

# Make the script executable
chmod +x agent.py

# Run the agent
./agent.py

What It Does

  1. Queries for ready work (no blocking dependencies)
  2. Claims the highest priority task
  3. "Works" on the task (simulated)
  4. If the task involves implementation, discovers a testing task
  5. Creates the new testing task and links it with discovered-from
  6. Completes the original task
  7. Repeats until no ready work remains

Example Output

🚀 Beads Agent starting...

============================================================
Iteration 1/10
============================================================

📋 Claiming task: bd-1
🤖 Working on: Implement user authentication (bd-1)
   Priority: 1, Type: feature

💡 Discovered: Missing test coverage for this feature
✨ Creating issue: Add tests for Implement user authentication
🔗 Linking bd-2 ← discovered-from ← bd-1
✅ Completing task: bd-1 - Implemented successfully

🔄 New work discovered and linked. Running another cycle...

Integration with Real Agents

To integrate with a real LLM-based agent:

  1. Replace simulate_work() with actual LLM calls
  2. Parse the LLM's response for discovered issues/bugs
  3. Use the issue ID to track context across conversations
  4. Export/import JSONL to share state across agent sessions

Advanced Usage

# Create an agent with custom behavior
agent = BeadsAgent()

# Find specific types of work
ready = agent.run_bd("ready", "--priority", "1", "--assignee", "bot")

# Create issues with labels
agent.run_bd("create", "New task", "-l", "urgent,backend")

# Query dependency tree
tree = agent.run_bd("dep", "tree", "bd-1")

See Also