A specialized skill that prevents LLM hallucinations by enforcing a documentation-first workflow for all code and configuration generation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install doc-accurate-codegen
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 doc-accurate-codegen 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 Documentation-Accurate Code Generation?
The Documentation-Accurate Code Generation skill is a critical framework designed to eliminate the common problem of AI hallucinations. In the world of Openclaw Skills, this tool acts as a technical gatekeeper, ensuring that an agent never writes code from memory. Instead, it mandates a process where documentation is fetched, parsed, and validated before a single line of code is produced.
By prioritizing technical truth over probabilistic guessing, this skill ensures that method names, parameter types, and return values are 100% accurate to the library or API being used. It is an essential component for developers who require production-grade reliability from their AI coding agents, providing a structured way to maintain documentation-to-code parity.
Documentation-Accurate Code Generation Use Cases
- Implementation of unfamiliar APIs where LLMs often guess parameter names
- Generating complex cloud configurations that must follow strict, version-specific schemas
- Feature development requiring the latest library versions not covered in the model's training data
- Auditing and validating legacy AI-generated code against current official documentation
How Documentation-Accurate Code Generation Works
- The skill identifies the specific tool, API, or configuration format required for the task.
- It locates the most authoritative documentation source, such as internal files, web-based API references, or man pages.
- The documentation is loaded and parsed to extract precise technical signatures and requirements.
- Implementation code is generated based strictly on the extracted signatures, ignoring hallucinated patterns.
- The generated output is cross-referenced against the original documentation to verify accuracy.
- A reference log is created to track which documentation sources were used, ensuring full transparency in the generation process.
Documentation-Accurate Code Generation Setup
To utilize this within the ecosystem of Openclaw Skills, ensure your environment is properly configured with the necessary binaries and environment variables.
# Ensure system dependencies are installed
# Requires: curl, jq, git
# Install the necessary node package
npm install axios
# Set the required API key for web search capabilities
export BRAVE_API_KEY="your_brave_api_key_here"
Documentation-Accurate Code Generation Data Schema & Taxonomy
The skill organizes its validation and reference tracking using a clear metadata taxonomy to ensure every generation is traceable.
| Data Point | Details |
|---|---|
| Source Path | The URL or local file path of the documentation used |
| API Signature | Extracted method names, parameter types, and return values |
| Validation Log | A checklist confirming method, parameter, and error handling accuracy |
| Version Tracking | The specific version of the API or tool referenced during generation |
Documentation-Accurate Code Generation Advanced Features
- Automatic Documentation Discovery: Intelligently identifies and fetches relevant docs based on the coding context.
- Multi-Source Cross-Referencing: Validates code against multiple documentation sources to resolve conflicts and ensure the highest authority.
- Real-time API Change Detection: Alerts the user if the documentation has changed since the last generation cycle.
- Example Extraction and Adaptation: Pulls functional examples directly from docs and adapts them to the current codebase while maintaining structural integrity.
SKILL.md
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