An autonomous programming system that decomposes requirements, performs deep analysis, and iterates through self-reflection to deliver production-ready code.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install auto-coding-correctversion
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 auto-coding-correctversion 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 Auto-Coding?
The Auto-Coding skill is a sophisticated autonomous programming system designed to transform high-level requirements into high-quality code. Built for Openclaw Skills, this agent goes beyond simple code generation by incorporating a deep analysis module that handles root cause analysis and pattern recognition. It operates with a structured lifecycle that includes requirement decomposition, iterative self-reflection, and a rigorous delivery standard check to ensure all output is secure, documented, and functional.
By leveraging advanced reasoning, the Auto-Coding system can intelligently adjust its workflow based on task complexity. Whether you are generating a simple file-renaming script or developing a complex Flask API, this skill within the Openclaw Skills ecosystem ensures that the final delivery meets professional engineering standards through its integrated testing and validation protocols.
Auto-Coding Use Cases
- Automatically generating Python scripts for batch file processing or data manipulation.
- Developing full-stack application components such as React UI components or backend API services.
- Refactoring existing codebases to implement new features like logging or enhanced error handling.
- Performing autonomous security and syntax audits on generated code blocks before deployment.
How Auto-Coding Works
- Requirement Decomposition: The system analyzes the task complexity (1-10) and creates a tailored execution plan.
- Logic Analysis: It identifies the necessary domain knowledge, tools, and potential technical challenges.
- Research and Search: The agent searches for documentation and best practices using integrated search tools.
- Implementation: Code is generated and written to the local workspace.
- Automated Testing: The system runs the code to verify basic functionality and identify runtime errors.
- Deep Analysis & Reflection: Using the deep analysis module, it identifies patterns and performs root cause analysis on any failures.
- Iterative Optimization: The agent refines the code based on its own reflections until it meets the required standards.
- Final Delivery Check: The output undergoes a strict 8-point check covering syntax, security, and documentation.
Auto-Coding Setup
To use this skill with Openclaw Skills, ensure you have Python 3.10 or higher installed. You will need to install the required dependencies:
pip install dashscope duckduckgo-search
The system automatically reads your LLM configuration from ~/.nanobot/config.json. You can then run the skill using the CLI command:
/auto-coding "your requirement here"
Auto-Coding Data Schema & Taxonomy
The Auto-Coding skill organizes its operations within the ~/.nanobot/workspace directory. It utilizes a modular file structure for its internal logic:
| File | Purpose |
|---|---|
| worker.py | The core workflow engine that manages the agent's lifecycle. |
| decomposer.py | Analyzes tasks and adjusts execution flow based on complexity. |
| self_reflect.py | Handles the iterative feedback loop for code improvement. |
| delivery_check.py | Executes the 8-point standard verification checklist. |
| deep_analysis.py | Provides root cause analysis and pattern recognition capabilities. |
Auto-Coding Advanced Features
- Multi-Mode Execution: Supports Quick (scripts), Standard (general tasks), and Deep (complex optimization) working modes.
- Intelligent Task Scaling: Dynamically scales execution time and depth based on a calculated complexity score.
- 8-Point Delivery Standard: Built-in verification for syntax, security, documentation, error handling, tests, functional integrity, TODO removal, and code style.
- Root Cause Analysis: Advanced debugging module that investigates why code fails and implements structural fixes during iterations.
SKILL.md
Loading
Related Openclaw Skills
Prompt Crafter
A professional-grade framework for engineering high-performance AI prompts using proven structural methodologies like RACE and Chain-of-Thought.
Sparkforge Site Deployer
A high-speed deployment utility for scaffolding and shipping static websites to production platforms in under five minutes.
cmux
A powerful terminal multiplexer controller that enables programmatic management of workspaces, surfaces, and notifications via a Unix socket API.
Skill Auto-Use
A protocol for AI agents to automatically trigger and execute installed skills based on conversation context and pre-defined rules.
Propel Code Review
An asynchronous code review skill that uses the Propel Review API to analyze Git diffs and provide actionable feedback for AI agents.
Job Application Automation Skill
A sophisticated AI-driven automation system that handles job discovery, resume tailoring, and ATS application submission.
Featured*
