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Accelerate your development automation with Overcut Playbooks — a curated collection of pre-built workflows that solve common engineering challenges. Each playbook is a complete, production-ready workflow that you can import directly into Overcut and customize for your team.
Browse the complete collection at🔗 https://github.com/overcut-ai/overcut-playbooks.

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What are Playbooks?

Playbooks are pre-configured workflows that combine multiple steps, agents, and actions to automate complex software development tasks. They’re designed to be imported, customized, and deployed quickly.

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Why Use Playbooks?

Playbooks save you time and reduce errors by providing battle-tested automation patterns:
  • 🚀 Get started in minutes — Import workflows instead of building from scratch
  • 🎯 Proven patterns — Workflows tested and refined by real teams
  • 🔧 Easy customization — Adapt prompts and steps to match your codebase
  • 📚 Learn by example — Study patterns to build your own workflows

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Browse Available Playbooks

The Overcut Playbooks repository contains workflows organized by category:

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Planning & Requirements

  • Requirements Document Generation — Automatically generates comprehensive requirements documents from feature requests with codebase analysis and iterative review
  • Technical Design Proposal — Generate detailed technical design documents from requirements, helping teams align before implementation

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Development & Implementation

  • Create PR from Design — Automatically creates implementation pull requests from approved design documents with phased implementation, real-time progress tracking, and comprehensive testing

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Code Quality & Review

  • Code Review — Automated comprehensive code review with inline comments and suggestions
  • Fix Review Comments — Automatically addresses code review feedback with structured implementation plans and real-time progress tracking
  • Auto PR Description — Automatically generates and updates pull request descriptions based on code changes, commits, and related issues
  • Auto Root Cause Analysis — Automatically analyze bugs and suggest fixes when issues are labeled
  • Auto Changelog Reminder — Reminds developers to update changelog on PRs
  • Auto Docs Update on Merge — Automatically updates documentation when PRs are merged
  • Implement Documentation from Issue — Automatically implements documentation updates based on issues, analyzing product PRs and creating documentation pull requests

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Security

  • Remediate CVEs — Analyzes CVEs with context-aware risk assessment, evaluates multiple remediation strategies with trade-offs, and creates comprehensive implementation plans

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Collaboration

  • Automated Ticket Triage — Automatically categorize and prioritize new issues, helping teams focus on high-impact work

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Migration & Refactoring

  • Migration Package — Complete multi-workflow system for migrating code between architectures or frameworks

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How to Use Playbooks

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Step 1: Choose a Playbook

Browse the playbooks repository and find a workflow that matches your needs. Each playbook folder contains:
  • workflow.json — The workflow definition you’ll import
  • README.md — Complete documentation and usage guide
  • Step prompt files — Editable instructions for each workflow step

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Step 2: Import to Overcut

1

Download the workflow file

Navigate to the playbook folder in the repository and download the workflow.json file.
2

Open Overcut Workflow Builder

In Overcut, go to the Workflow Builder and click Import Workflow.
3

Upload the JSON file

Select the downloaded workflow.json file to import the workflow structure.
4

Map agents

Update agent references to match your Overcut agent configuration. The playbook uses example agent IDs that you’ll need to map to your actual agents.

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Step 3: Customize for Your Team

Each playbook includes editable prompt files that you can modify to match your codebase conventions, coding standards, and team preferences.
AI-Assisted Customization: Use AI to help adapt prompts to your specific codebase. Ask AI to update the workflow based on your team’s conventions, or modify individual step prompts to focus on specific areas like security, performance, or API design.

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Example: Code Review Playbook

The Code Review playbook demonstrates how to automate comprehensive pull request reviews. Here’s what it does:
  1. Listens for new pull requests — Automatically triggers when PRs are opened
  2. Plans the review — Analyzes changes and creates a structured review plan
  3. Executes inline review — Posts detailed comments directly on the PR
  4. Handles feedback — Responds to developer comments and can implement fixes
Business Value:
  • Reduces review time by 60-80% for routine changes
  • Ensures consistent review standards across all PRs
  • Catches issues early before they reach production
  • Frees senior developers to focus on architecture and complex problems

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Example: Requirements Document Generation

The Requirements Document Generation playbook automatically creates comprehensive requirements documents from feature requests. It:
  1. Analyzes the feature request — Understands the user’s needs and context
  2. Explores the codebase — Identifies related code, existing patterns, and dependencies
  3. Generates structured requirements — Creates detailed, actionable specifications
  4. Iterates with feedback — Refines the document based on stakeholder input
Business Value:
  • Saves 4-8 hours per feature on requirements documentation
  • Ensures nothing is missed by systematically analyzing the codebase
  • Creates consistent, professional documentation
  • Reduces back-and-forth by catching edge cases early

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Example: Auto Root Cause Analysis

The Auto Root Cause Analysis playbook automatically investigates bugs when issues are labeled. It:
  1. Analyzes the bug report — Understands symptoms and context
  2. Investigates the codebase — Traces through code to find root causes
  3. Suggests fixes — Provides actionable solutions with explanations
  4. Posts findings — Shares analysis directly in the issue thread
Business Value:
  • Reduces debugging time by 50-70%
  • Helps junior developers learn from systematic analysis
  • Surfaces patterns across multiple bugs
  • Enables faster resolution with clear fix suggestions

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Customizing Playbooks

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Understanding Playbook Structure

Each playbook folder contains: 
playbook-name/
├── workflow.json          # Import this into Overcut
├── README.md              # Documentation and usage guide
├── step-id-name.md        # Prompt for step (filename = step ID)
├── another-step-id.md     # Each prompt file matches its step ID
└── special-agents/        # (Optional) Specialized agent instructions
    └── agent-name.md      # Instructions for configuring custom agents

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Editing Prompts

Prompt filenames match step IDs in workflow.json, enabling AI-assisted updates:
  1. Edit the markdown file for the step you want to change
  2. Use AI to update the workflow.json file to match your changes
  3. Re-import the updated workflow into Overcut
Bidirectional Editing: You can edit prompts in the markdown files and have AI update the workflow, or modify the workflow in Overcut and export it back. The naming convention (step ID = filename) makes this seamless.

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Special Agents

Some workflows require specialized agents with domain-specific expertise. When a playbook needs agents like “Security Engineer” or “Database Architect”, you’ll find configuration instructions in the special-agents/ folder.

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Best Practices

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Start Simple

Begin with a single playbook that addresses your most immediate need. Once you’re comfortable with the workflow, expand to additional playbooks.

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Customize Gradually

Import the playbook as-is first, test it, then customize prompts to match your team’s style. This helps you understand the workflow before making changes.

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Monitor and Iterate

Track how playbooks perform in your environment. Adjust prompts based on what works and what doesn’t. Each team’s codebase and culture is unique.

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Combine Playbooks

Many playbooks work well together. For example:
  • Requirements Document Generation → Technical Design Proposal → Create PR from Design
  • Auto Root Cause Analysis → Fix Review Comments (when fixes are needed)

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Next Steps

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Contributing

Found a playbook that works great for your team? Consider contributing improvements back to the community! The playbooks repository welcomes:
  • New playbooks for common workflows
  • Improvements to existing playbooks
  • Better prompts and documentation
  • Bug fixes and edge case handling
See the Contributing Guide for details.