A standardized coding workflow for AI agents that enforces planning, implementation, and rigorous verification for high-quality software development.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install openclaw-code
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 openclaw-code 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 Code AI Workflow?
The Code skill is a comprehensive framework designed to transform AI agents into disciplined software developers. By implementing a structured lifecycle—moving from planning to delivery—it ensures that every line of code is intentional and verifiable. This Openclaw Skills extension prioritizes user control and local execution, focusing on maintaining clean codebases while adhering to persistent user preferences stored in a dedicated local memory file. It bridges the gap between chaotic AI code generation and professional engineering standards.
Code AI Workflow Use Cases
- Structured implementation of new features in complex software projects.
- Developing test-driven code where verification is mandatory at every step of the process.
- Maintaining long-term development preferences across multiple sessions using local memory storage.
- Breaking down complex architectural requests into manageable, testable planning sequences.
How Code AI Workflow Works
- The agent first checks the local ~/code/memory.md file to align with specific user coding preferences and global constraints.
- Upon receiving a user request, the skill initiates a planning phase to break the task into small, independently verifiable sub-steps.
- Implementation proceeds guided by the plan, focusing on one testable unit at a time to maintain high code quality.
- After each coding step, the skill triggers a verification phase, suggesting automated tests or manual checks before moving forward.
- Once all steps are completed and verified, the final code is delivered according to the user criteria.
Code AI Workflow Setup
To initialize the Code skill for your Openclaw Skills environment, set up the local directory structure using the following commands:
mkdir -p ~/code
touch ~/code/memory.md
Ensure your agent has read and write permissions for the ~/code/ directory to enable persistent preference storage.
Code AI Workflow Data Schema & Taxonomy
The skill organizes its operational data and user preferences locally within the ~/code/ directory using a simple but effective file-based taxonomy:
| File | Purpose |
|---|---|
| memory.md | Stores persistent user preferences and "Never" rules explicitly requested by the user. |
| planning.md | Provides templates and patterns for breaking down complex coding tasks. |
| state.md | Tracks the current progress and state of multi-task coding workflows. |
| criteria.md | Defines the specific success metrics and user criteria for task verification. |
Code AI Workflow Advanced Features
- Persistent local memory allows your agent to learn your coding style and prohibited patterns over time without external cloud storage.
- Granular state management enables the agent to handle multi-step refactoring projects without losing context between sessions.
- Verification-first workflow ensures that UI changes or logic updates are backed by screenshots or test results before delivery.
- Zero-network architecture guarantees that your project data and preferences stay local and secure.
SKILL.md
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