A comprehensive coding workflow skill that guides AI agents through planning, implementation, and rigorous verification of software projects.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install 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 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 Skill for AI Agents?
The Code skill provides a professional framework for AI-driven software development, prioritizing structure and reliability. It transforms vague requests into actionable, testable steps by enforcing a Plan-Execute-Verify-Deliver lifecycle. By integrating this skill into Openclaw Skills, developers ensure that their AI agents don't just write code, but follow a disciplined architecture that respects user preferences and project constraints.
At its core, this skill is designed for privacy and user control. It operates entirely on local data, storing persistent preferences in a dedicated directory and never executing commands or making network requests autonomously. This ensures that the developer remains the final authority on every change made to the codebase.
Code Skill for AI Agents Use Cases
- Managing complex software implementation requests through structured task breakdowns.
- Enforcing consistent coding standards and preferences across multiple sessions.
- Orchestrating multi-step development tasks that require state tracking and progress monitoring.
- Ensuring all code changes are verified via tests or visual inspections before final delivery.
How Code Skill for AI Agents Works
- The agent first reads the memory.md file to align with the user's explicit preferences and constraints.
- Upon a coding request, the agent generates a comprehensive plan, breaking the task into independent, testable units.
- The agent executes the plan step-by-step, seeking user guidance and approval for each phase.
- After implementation, the skill triggers a verification workflow, suggesting specific tests or screenshots to validate functionality.
- The process concludes with a final delivery check against the user's original criteria and project state.
Code Skill for AI Agents Setup
To begin using this skill within the Openclaw Skills environment, you need to set up the local storage directory for preference persistence.
# Create the dedicated code memory directory
mkdir -p ~/code
# Initialize the memory file for preferences
touch ~/code/memory.md
Once the directory is created, the AI agent will automatically utilize it to store information like 'Never use X library' or 'Always format with Y' when explicitly requested by the user.
Code Skill for AI Agents Data Schema & Taxonomy
The skill manages several key reference and data files to maintain the integrity of the development workflow within Openclaw Skills:
| File | Purpose |
|---|---|
memory.md |
A persistent store for user-provided preferences and explicit 'Never' constraints. |
planning.md |
Templates and patterns for breaking down complex coding tasks. |
state.md |
Tracks the current status and progress of multi-step development workflows. |
verification.md |
Standardized protocols for testing functions and UI changes. |
criteria.md |
Stores specific user-defined success metrics for the current project. |
Code Skill for AI Agents Advanced Features
- Explicit Preference Learning: Dynamically updates the local memory file when the user provides specific stylistic or technical feedback.
- Multi-Agent Coordination: Supports sub-agent delegation for specialized tasks, provided the user gives explicit authorization.
- State Persistence: Maintains the context of complex refactors or features across different sessions using the state.md file.
- Zero-Network Architecture: Ensures complete security by prohibiting external network requests and keeping all data within the local project scope.
SKILL.md
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