README Grader for Openclaw

An expert evaluation tool that audits README files against open-source best practices to provide a numerical score and actionable improvement roadmap.

sunny0826
v1.0.0
Apr 2, 2026
0
760
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install readme-grader

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install readme-grader 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 README Grader?

README Grader is a specialized utility within the Openclaw Skills ecosystem designed to act as an automated Open Source Maintainer and Developer Advocate. It meticulously analyzes the textual content of a README file to ensure it meets the high standards required for modern software projects. By focusing on clarity, accessibility, and professional presentation, this skill helps developers transform basic documentation into a high-quality gateway for their users and contributors.

This skill is particularly valuable for developers looking to boost engagement on repositories. It provides a standardized framework for documentation quality, ensuring that critical elements like installation steps, usage examples, and contribution guidelines are not only present but effective. By using Openclaw Skills like this one, teams can maintain a consistent professional image across all their public-facing codebases.

README Grader Use Cases

  • Benchmarking existing project documentation against industry standards.
  • Preparing a repository for a public launch or submission to a registry.
  • Identifying missing critical components like license information or contribution guides.
  • Generating optimization examples to show team members how to improve their Markdown formatting.
  • Auditing third-party libraries to assess their documentation quality before adoption.

How README Grader Works

  1. The user provides the raw Markdown text of the README they wish to evaluate to the Openclaw Skills agent.
  2. The skill performs a security sweep to treat the input strictly as textual data, preventing any embedded instruction injection.
  3. The agent analyzes the text across five core dimensions: Project Overview, Quick Start, Usage Guides, Community Guidelines, and Formatting.
  4. A score is assigned to each category based on specific criteria like the presence of badges, copy-pasteable code, and TOC inclusion.
  5. The skill generates a comprehensive report including a total score out of 100, specific pros/cons, and a Markdown snippet demonstrating the recommended optimizations.

README Grader Setup

To use this README Grader within your Openclaw Skills environment, ensure your agent has access to the skill definition. Users should provide the text directly:

# Example of how to prompt the agent
"Please grade this README content for me: [Paste your README text here]"

Note: For security reasons, do not provide URLs. Always provide the raw text content directly to the session.

README Grader Data Schema & Taxonomy

The skill evaluates data based on a 100-point taxonomy across five key dimensions:

Dimension Weight Criteria
Project Overview 20 pts Title, concise description, badges, value prop
Quick Start 20 pts Prerequisites, step-by-step installation
Usage Guides 20 pts Examples, expected output, visual aids
Community 20 pts Contributing.md, Code of Conduct, issue reporting
Structure 20 pts TOC, License statement, Markdown hygiene

README Grader Advanced Features

  • Context-aware feedback based on the specific type of project (e.g., visual tool vs. CLI).
  • Indirect prompt injection protection via strict data-as-text sanitization.
  • Automated generation of 'Optimization Examples' providing ready-to-use Markdown code blocks.
  • Multilingual support for the evaluation report (defaulting to Chinese as per configuration).
  • Seamless integration into broader Openclaw Skills workflows for repository management.

SKILL.md


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