Prodigy 🚀

Transform ad-hoc Claude sessions into reproducible development pipelines with parallel execution, automatic retry, and full state management.

Table of Contents

• Features
• Installation
  • Using Cargo (Recommended)
  • From Source
• Quick Start
  • Your First Workflow
  • Parallel Execution Example
• Usage
  • Basic Commands
  • Advanced Workflows
  • Configuration
• Examples
  • Automated Testing Pipeline
  • Parallel Code Analysis
• Documentation
• Troubleshooting
• Contributing
• License
• Acknowledgments

Features

• ✨ Workflow Orchestration - Define complex development workflows in simple YAML
• ⚡ Parallel Execution - Run multiple Claude agents simultaneously with MapReduce
• 🔄 Automatic Retry - Smart retry strategies with exponential backoff and circuit breakers
• 💾 Full State Management - Checkpoint and resume interrupted workflows exactly where they left off
• 🌳 Git Integration - Automatic worktree isolation for every workflow execution with commit tracking
• 🛡️ Error Recovery - Comprehensive failure handling with on-failure handlers
• 📊 Analytics - Cost tracking, performance metrics, and optimization recommendations
• 🔧 Extensible - Custom validators, handlers, and workflow composition
• 📚 Documentation - Comprehensive man pages and built-in help system

Installation

Using Cargo (Recommended)

cargo install prodigy

From Source

# Clone the repository
git clone https://github.com/iepathos/prodigy
cd prodigy

# Build and install
cargo build --release
cargo install --path .

# Optional: Install man pages
./scripts/install-man-pages.sh

Quick Start

Get up and running in under 5 minutes with these simple examples.

Your First Workflow

1. Initialize Prodigy in your project:

prodigy init

2. Create a simple workflow (fix-tests.yml):

name: fix-failing-tests
steps:
  - shell: "cargo test"
    on_failure:
      claude: "/fix-test-failures"
      max_attempts: 3

3. Run the workflow:

prodigy run fix-tests.yml

Parallel Execution Example

Process multiple files simultaneously with MapReduce:

name: add-documentation
mode: mapreduce

setup:
  - shell: "find src -name '*.rs' -type f > files.json"

map:
  input: files.json
  agent_template:
    - claude: "/add-rust-docs ${item}"
  max_parallel: 10

reduce:
  - claude: "/summarize Documentation added to ${map.successful} files"

Run with:

prodigy run add-documentation.yml

Usage

Basic Commands

# Run a workflow
prodigy run workflow.yml

# Execute a single command with retries
prodigy exec "claude: /refactor main.rs" --retry 3

# Process files in parallel
prodigy batch "*.py" --command "claude: /add-types" --parallel 5

# Resume an interrupted workflow
prodigy resume workflow-123

# View analytics and costs
prodigy analytics --session abc123

# Manage worktrees (all workflow executions use isolated git worktrees by default)
prodigy worktree ls                    # List active worktrees
prodigy worktree ls --detailed        # Show enhanced session information
prodigy worktree ls --json            # Output in JSON format
prodigy worktree ls --detailed --json # Combine detailed info with JSON output
prodigy worktree clean                # Clean up inactive worktrees

Template Management

Prodigy supports reusable workflow templates that can be registered, shared, and invoked with parameters. This enables building a library of common workflows and patterns.

Template Commands

# Initialize a template directory
prodigy template init templates/

# Register a template from a file
prodigy template register my-workflow.yml \
  --name refactor-pipeline \
  --description "Refactoring workflow with tests" \
  --version 1.0.0 \
  --tags refactor,testing \
  --author "Your Name"

# List all registered templates
prodigy template list
prodigy template list --long           # Show detailed information
prodigy template list --tag refactor   # Filter by tag

# Show template details
prodigy template show refactor-pipeline

# Search for templates
prodigy template search "refactor"
prodigy template search testing --by-tag

# Validate a template file
prodigy template validate my-workflow.yml

# Delete a template
prodigy template delete refactor-pipeline --force

Creating Templates

Templates are standard workflow files with parameter definitions:

name: refactor-with-tests
description: Refactor code and ensure tests pass
version: 1.0.0

parameters:
  target:
    description: File or directory to refactor
    type: string
    required: true
  test_command:
    description: Command to run tests
    type: string
    default: "cargo test"

commands:
  - claude: "/refactor ${target}"
  - shell: "${test_command}"
    on_failure:
      claude: "/fix-test-failures"
      max_attempts: 3

Using Templates with Parameters

Pass parameters via CLI flags or parameter files:

# Pass parameters individually
prodigy run refactor-pipeline.yml \
  --param target=src/main.rs \
  --param test_command="cargo test --all"

# Pass parameters from a JSON file
prodigy run refactor-pipeline.yml \
  --param-file params.json

# Pass parameters from a YAML file
prodigy run refactor-pipeline.yml \
  --param-file params.yaml

Parameter file example (params.json):

{
  "target": "src/main.rs",
  "test_command": "cargo test --all",
  "timeout": 300
}

Parameter file example (params.yaml):

target: src/main.rs
test_command: cargo test --all
timeout: 300

Parameter Type Inference:

• Numbers (integer and float) are automatically detected
• Booleans (true/false) are parsed correctly
• Strings are the default type
• CLI parameters override file parameters

Parameter Substitution: Parameters are available in commands using ${parameter_name} syntax:

• ${target} - Direct parameter reference
• ${test_command} - Parameter with default value
• CLI and file parameters are merged (CLI takes precedence)

Advanced Workflows

Retry Configuration

retry_defaults:
  attempts: 3
  backoff: exponential
  initial_delay: 2s
  max_delay: 30s
  jitter: true

steps:
  - shell: "deploy.sh"
    retry:
      attempts: 5
      backoff:
        fibonacci:
          initial: 1s
      retry_on: [network, timeout]
      retry_budget: 5m

Environment Management

env:
  NODE_ENV: production
  WORKERS:
    command: "nproc"
    cache: true

secrets:
  API_KEY: ${vault:api/keys/production}

steps:
  - shell: "npm run build"
    env:
      BUILD_TARGET: production
    working_dir: ./frontend

Workflow Composition

imports:
  - path: ./common/base.yml
    alias: base

templates:
  test-suite:
    parameters:
      - name: language
        type: string
    steps:
      - shell: "${language} test"

workflows:
  main:
    extends: base.default
    steps:
      - use: test-suite
        with:
          language: cargo

Git Context Variables

Prodigy automatically tracks git changes during workflow execution and provides context variables for accessing file changes, commits, and statistics:

Step-level Variables (Current Step)

• ${step.files_added} - Files added in the current step
• ${step.files_modified} - Files modified in the current step
• ${step.files_deleted} - Files deleted in the current step
• ${step.files_changed} - All files changed (added + modified + deleted)
• ${step.commits} - Commit hashes created in the current step
• ${step.commit_count} - Number of commits in the current step
• ${step.insertions} - Lines inserted in the current step
• ${step.deletions} - Lines deleted in the current step

Workflow-level Variables (Cumulative)

• ${workflow.files_added} - All files added across the workflow
• ${workflow.files_modified} - All files modified across the workflow
• ${workflow.files_deleted} - All files deleted across the workflow
• ${workflow.files_changed} - All files changed across the workflow
• ${workflow.commits} - All commit hashes across the workflow
• ${workflow.commit_count} - Total commits across the workflow
• ${workflow.insertions} - Total lines inserted across the workflow
• ${workflow.deletions} - Total lines deleted across the workflow

Pattern Filtering

Variables support pattern filtering using glob patterns:

# Get only markdown files added
- shell: "echo '${step.files_added:*.md}'"

# Get only Rust source files modified
- claude: "/review ${step.files_modified:*.rs}"

# Get specific directory changes
- shell: "echo '${workflow.files_changed:src/*}'"

Format Modifiers

Control output format with modifiers:

# JSON array format
- shell: "echo '${step.files_added:json}'"  # ["file1.rs", "file2.rs"]

# Newline-separated (for scripts)
- shell: "echo '${step.files_added:lines}'" # file1.rs\nfile2.rs

# Comma-separated
- shell: "echo '${step.files_added:csv}'"   # file1.rs,file2.rs

# Space-separated (default)
- shell: "echo '${step.files_added}'"       # file1.rs file2.rs

Example Usage

name: code-review-workflow
steps:
  # Make changes
  - claude: "/implement feature X"
    commit_required: true

  # Review only the changed Rust files
  - claude: "/review-code ${step.files_modified:*.rs}"

  # Generate changelog for markdown files
  - shell: "echo 'Changed docs:' && echo '${step.files_added:*.md:lines}'"

  # Conditional execution based on changes
  - shell: "cargo test"
    when: "${step.files_modified:*.rs}"  # Only run if Rust files changed

  # Summary at the end
  - claude: |
      /summarize-changes
      Total files changed: ${workflow.files_changed:json}
      Commits created: ${workflow.commit_count}
      Lines added: ${workflow.insertions}
      Lines removed: ${workflow.deletions}

Workflow Syntax

Write File Command

The write_file command allows workflows to create files with content, supporting multiple formats with validation and automatic formatting.

Basic Syntax:

- write_file:
    path: "output/results.txt"
    content: "Processing complete!"
    format: text  # text, json, or yaml
    mode: "0644"  # Unix permissions (default: 0644)
    create_dirs: false  # Create parent directories (default: false)

Supported Formats:

1. Text (default) - Plain text with no processing:

- write_file:
    path: "logs/build.log"
    content: "Build started at ${timestamp}"
    format: text

2. JSON - Validates and pretty-prints JSON:

- write_file:
    path: "output/results.json"
    content: '{"status": "success", "items_processed": ${map.total}}'
    format: json
    create_dirs: true

3. YAML - Validates and formats YAML:

- write_file:
    path: "config/settings.yml"
    content: |
      environment: production
      server:
        port: 8080
        host: localhost
    format: yaml

Variable Interpolation:

All fields support variable interpolation:

# In MapReduce map phase
- write_file:
    path: "output/${item.name}.json"
    content: '{"id": "${item.id}", "processed": true}'
    format: json
    create_dirs: true

# In reduce phase
- write_file:
    path: "summary.txt"
    content: "Processed ${map.total} items, ${map.successful} successful"
    format: text

Security Features:

• Path traversal protection (rejects paths containing ..)
• JSON/YAML validation before writing
• Configurable file permissions (Unix systems only)

Common Use Cases:

1. Aggregating MapReduce results:

reduce:
  - write_file:
      path: "results/summary.json"
      content: '{"total": ${map.total}, "successful": ${map.successful}, "failed": ${map.failed}}'
      format: json

2. Generating configuration files:

- write_file:
    path: ".config/app.yml"
    content: |
      name: ${PROJECT_NAME}
      version: ${VERSION}
      features:
        - authentication
        - caching
    format: yaml

3. Creating executable scripts:

- write_file:
    path: "scripts/deploy.sh"
    content: |
      #!/bin/bash
      echo "Deploying ${APP_NAME}"
      ./deploy.sh --env production
    mode: "0755"
    create_dirs: true

Validation and Error Recovery

Prodigy supports multi-step validation and error recovery with two formats:

Array Format (for simple command sequences):

validate:
  - shell: "prep-command-1"
  - shell: "prep-command-2"
  - claude: "/validate-result"

Object Format (when you need metadata like threshold, max_attempts, etc.):

validate:
  commands:
    - shell: "prep-command-1"
    - shell: "prep-command-2"
    - claude: "/validate-result"
  result_file: "validation-results.json"
  threshold: 75  # Validation must score at least 75/100
  on_incomplete:
    commands:
      - claude: "/fix-gaps --gaps ${validation.gaps}"
      - shell: "rebuild-and-revalidate.sh"
    max_attempts: 3
    fail_workflow: false

Key Points:

• Use array format when you only need to run commands
• Use object format when you need to set threshold, result_file, max_attempts, or fail_workflow
• Fields like threshold and max_attempts belong at the config level, not on individual commands
• on_incomplete supports the same two formats (array or object with commands:)

Example: Multi-step validation workflow

- claude: "/implement-feature spec.md"
  commit_required: true
  validate:
    commands:
      - shell: "cargo test"
      - shell: "cargo clippy"
      - claude: "/validate-implementation spec.md"
    result_file: ".prodigy/validation.json"
    threshold: 90
    on_incomplete:
      commands:
        - claude: "/fix-issues --gaps ${validation.gaps}"
        - shell: "cargo test"
      max_attempts: 5
      fail_workflow: true

Configuration

Prodigy looks for configuration in these locations (in order):

1. .prodigy/config.yml - Project-specific configuration
2. ~/.config/prodigy/config.yml - User configuration
3. /etc/prodigy/config.yml - System-wide configuration

Example configuration:

# .prodigy/config.yml
claude:
  model: claude-3-opus
  max_tokens: 4096

worktree:
  max_parallel: 20
  cleanup_policy:
    idle_timeout: 300
    max_age: 3600

retry:
  default_attempts: 3
  default_backoff: exponential

storage:
  events_dir: ~/.prodigy/events
  state_dir: ~/.prodigy/state

Examples

Example 1: Automated Testing Pipeline

Fix all test failures automatically with intelligent retry:

name: test-pipeline
steps:
  - shell: "cargo test"
    on_failure:
      - claude: "/analyze-test-failure ${shell.output}"
      - claude: "/fix-test-failure"
      - shell: "cargo test"
    retry:
      attempts: 3
      backoff: exponential

  - shell: "cargo fmt -- --check"
    on_failure: "cargo fmt"

  - shell: "cargo clippy -- -D warnings"
    on_failure:
      claude: "/fix-clippy-warnings"

Example 2: Parallel Code Analysis

Analyze and improve multiple files concurrently:

name: parallel-analysis
mode: mapreduce

setup:
  - shell: |
      find . -name "*.rs" -exec wc -l {} + |
      sort -rn |
      head -20 |
      awk '{print $2}' > complex-files.json

map:
  input: complex-files.json
  agent_template:
    - claude: "/analyze-complexity ${item}"
    - claude: "/suggest-refactoring ${item}"
    - shell: "cargo test --lib $(basename ${item} .rs)"
  max_parallel: 10

reduce:
  - claude: "/generate-refactoring-report ${map.results}"
  - shell: "echo 'Analyzed ${map.total} files, ${map.successful} successful'"

Documentation

📚 Full documentation is available at https://iepathos.github.io/prodigy

Quick links:

• Getting Started
• Workflow Basics
• MapReduce Guide
• Command Reference
• Examples

Building Documentation Locally

# Install mdBook
cargo install mdbook

# Serve with live reload
mdbook serve book --open

Additional Resources

• 📝 Workflow Syntax (Single Page) - Complete syntax reference in one file
• 🏗️ Architecture - System design and internals
• 🤝 Contributing Guide - How to contribute to Prodigy
• 📚 Man Pages - Unix-style manual pages for all commands

Quick Reference

Troubleshooting

Common Issues and Solutions

prodigy run workflow.yml --max-parallel 20

prodigy run workflow.yml -v

prodigy analytics --session <session-id>

# List available checkpoints
prodigy checkpoints list

# Resume from latest checkpoint
prodigy resume

# Resume specific workflow
prodigy resume workflow-abc123

# View failed items
prodigy dlq view <job-id>

# Reprocess failed items
prodigy dlq retry <job-id> --max-parallel 5

# Show effective configuration
prodigy config show

# Validate configuration
prodigy config validate

cd prodigy
./scripts/install-man-pages.sh

# Or install to user directory
./scripts/install-man-pages.sh --user

# Set log level
export RUST_LOG=debug
prodigy run workflow.yml -vv

# View detailed events
prodigy events --job-id <job-id> --verbose

prodigy run workflow.yml
# Shows progress and results, but no Claude JSON streaming output

prodigy run workflow.yml -v
# Shows Claude streaming JSON output for debugging interactions

prodigy run workflow.yml -vv
prodigy run workflow.yml -vvv
# Also shows Claude streaming output plus additional internal logs

PRODIGY_CLAUDE_CONSOLE_OUTPUT=true prodigy run workflow.yml
# Shows Claude streaming output regardless of verbosity level

Getting Help

• 🐛 Report Issues
• 💬 Discussions
• 📧 Email Support

Contributing

We welcome contributions! Please see our Contributing Guide for details.

Quick Start for Contributors

# Fork and clone the repository
git clone https://github.com/YOUR-USERNAME/prodigy
cd prodigy

# Set up development environment
cargo build
cargo test

# Run with verbose output
RUST_LOG=debug cargo run -- run test.yml

# Before submitting PR
cargo fmt
cargo clippy -- -D warnings
cargo test

Areas We Need Help

• 📦 Package manager distributions (brew, apt, yum)
• 🌍 Internationalization and translations
• 📚 Documentation and examples
• 🧪 Testing and bug reports
• ⚡ Performance optimizations
• 🎨 UI/UX improvements

License

Prodigy is licensed under MIT. See LICENSE for details.

Acknowledgments

Prodigy builds on the shoulders of giants:

• Claude Code CLI - The AI pair programmer that powers Prodigy
• Tokio - Async runtime for Rust
• Clap - Command-line argument parsing
• Serde - Serialization framework

Special thanks to all contributors who have helped make Prodigy better!

Made with ❤️ by developers, for developers

Features • Quick Start • Docs • Contributing