A pragmatic skill for AI agents to write concise, direct, and high-quality code using industry-standard principles.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install clean-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 clean-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 Clean Code - Pragmatic AI Coding Standards?
This skill enforces pragmatic coding standards for AI agents, ensuring output is focused on the solution rather than explanations. It integrates core principles like SRP, DRY, KISS, and YAGNI to maintain code quality and readability. By using this tool within Openclaw Skills, developers can ensure their AI agents produce production-ready code that follows strict naming conventions and structural patterns like guard clauses and flat nesting.
Beyond just writing code, it transforms the AI from a conversational assistant into a precise engineering tool. It mandates a philosophy where code should be self-documenting, eliminating the need for verbose comments or "programming lessons" during the development cycle. This approach significantly reduces noise and increases the velocity of feature delivery and bug fixing.
Clean Code - Pragmatic AI Coding Standards Use Cases
- Enforcing consistent naming conventions and SCREAMING_SNAKE constants across a codebase.
- Reducing technical debt by applying DRY and KISS principles automatically during code generation.
- Refactoring large, complex "God functions" into small, single-responsibility units under 20 lines.
- Streamlining AI agent interactions by prioritizing direct code updates over conversational fluff.
- Ensuring dependency safety and preventing broken imports when editing shared components or service files.
How Clean Code - Pragmatic AI Coding Standards Works
- The agent analyzes the task requirements and identifies the specific files to be modified based on the requested feature or bug fix.
- It performs a mandatory dependency check to understand which files import or are imported by the target file to prevent breaking changes.
- The skill applies core coding principles such as guard clauses, composition, and flat nesting to the logic structure.
- The agent writes the code directly into the target files, strictly avoiding unnecessary comments or introductory "First we import..." text.
- Mandatory verification scripts are executed to validate linting, type coverage, and specific domain audits based on the agent's role.
- The agent captures all script output, summarizes errors or warnings, and asks for user confirmation before proceeding with fixes.
Clean Code - Pragmatic AI Coding Standards Setup
To integrate this skill into your environment, ensure your AI agent is pointed to the correct skill path within your repository structure.
# Clone or add the skill to your agent configuration directory
mkdir -p .agent/skills/
cp -r ./path-to-clean-code .agent/skills/clean-code
# Ensure Python environment is ready for validation scripts
pip install -r .agent/skills/clean-code/requirements.txt
Clean Code - Pragmatic AI Coding Standards Data Schema & Taxonomy
The skill organizes its logic around a strict set of rules and verification mappings. Below is the taxonomy used for data organization:
| Component | Description |
|---|---|
| Core Principles | Definition of SRP, DRY, KISS, YAGNI, and Boy Scout rules. |
| Naming Rules | Intent-revealing conventions for variables, functions, and booleans. |
| Function Rules | Constraints for line length (max 20) and argument count (max 3). |
| Verification Mapping | Association between agent roles (e.g., seo-specialist) and specific Python audit scripts. |
| Checklists | Mandatory self-check tables for goal completion and error-free delivery. |
Clean Code - Pragmatic AI Coding Standards Advanced Features
- Multi-agent validation mapping that ensures only qualified agents run specific domain audits (e.g., security scans vs. UX audits).
- Mandatory Read-Summarize-Ask workflow which prevents AI agents from auto-fixing errors without explicit user consent.
- Intelligent dependency tracking that forces the agent to edit all affected files within a single task to maintain system integrity.
- Strict anti-pattern detection that automatically identifies and removes magic numbers, deep nesting, and redundant helper functions.
- Integration with Openclaw Skills to provide a standardized verification output format for all validation scripts.
SKILL.md
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