An autonomous project execution skill that processes structured plans to code, test, and commit changes without human intervention.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ai-c-plan
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ai-c-plan using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is AI-C Plan: Autonomous Project Execution?
The AI-C Plan skill is a sophisticated automation engine designed for Openclaw Skills. It reads project roadmaps from Markdown or CSV files and executes them step-by-step. By analyzing dependencies and priorities, it ensures a logical development flow, handling everything from monorepo initialization to UI alignment and database migrations. It operates in an autopilot mode, reducing manual overhead for developers while maintaining high standards of code quality and architectural integrity through strict adherence to system prompts.
This skill is particularly effective for developers who need to bridge the gap between high-level project planning and low-level implementation. By integrating with Openclaw Skills, it provides a seamless bridge between structured project documentation and real-world code execution, ensuring that every commit is verified and aligned with the intended architecture.
AI-C Plan: Autonomous Project Execution Use Cases
- Full-cycle project initialization from a structured roadmap or CSV file
- Automated monorepo management and package configuration
- Hands-free UI development with reference-based styling and design alignment
- Database schema migrations and management using Prisma or similar tools
- Continuous development, linting, and testing in isolated environments
How AI-C Plan: Autonomous Project Execution Works
- The agent reads the project plan from designated Markdown or CSV files located in the plan directory.
- It extracts all tasks and builds a Directed Acyclic Graph (DAG) to determine the optimal execution order based on dependencies and priorities (P0-P3).
- Before each step, it performs pre-execution checks against the AI_CONSULTANT_SYSTEM_PROMPT to ensure technical alignment with the architecture.
- Code is generated, files are modified, and commands are executed (lint/test/build) according to the specific requirements of the current step.
- Database migrations are automatically generated and applied if schema changes are detected.
- Upon success, changes are committed to the repository using the Conventional Commit format.
- Progress is tracked in a central progress.json file, updating the task status to Done or Blocked as required.
AI-C Plan: Autonomous Project Execution Setup
To integrate this into your local environment as part of your Openclaw Skills workflow, ensure your project follows the expected folder structure and has the required plan files.
# Ensure the plan directory exists for your roadmap files
mkdir -p plan
# Create the directory for progress tracking
mkdir -p /home/adige/AI-C/
touch /home/adige/AI-C/progress.json
# Initialize the environment templates
cp .env.example .env
AI-C Plan: Autonomous Project Execution Data Schema & Taxonomy
The AI-C Plan skill utilizes a structured data approach to manage the project lifecycle within the Openclaw Skills ecosystem:
| Data Component | Format | Description |
|---|---|---|
| Plan Files | MD/CSV | Contains task IDs (ST-*), priorities, and dependencies. |
| progress.json | JSON | The single source of truth for task completion status. |
| Architecture Docs | Markdown | System prompts that define the tech stack and monorepo rules. |
| .env.example | Text | Templates for managing external service configurations and placeholders. |
AI-C Plan: Autonomous Project Execution Advanced Features
- Autopilot mode enables continuous execution of the entire project plan without requiring manual user confirmation for each step.
- Smart DEV_FALLBACK_MODE allows the agent to use mock providers or stubs when real secrets are missing, preventing workflow interruptions.
- Visual UI alignment capabilities allow the agent to inspect design files and images to ensure the frontend matches reference materials.
- Priority-based scheduling ensures that P0 (Critical) tasks are completed before lower-priority features, even within the same dependency level.
- Automated Git lifecycle management ensures every incremental change is documented with clean, standardized commit messages.
SKILL.md
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