A professional quality-control skill for Openclaw Skills designed to generate, validate, and manage high-quality pull requests that maintainers love.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pull-request
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 pull-request 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 Pull Request Skill?
The Pull Request skill serves as an intelligent intermediary between your code changes and a repository's main branch. Integrated within the Openclaw Skills ecosystem, it acts as a quality filter to ensure that every contribution is polished, adheres to project-specific guidelines, and respects maintainer time. By analyzing repository context and following strict pre-submission protocols, it helps developers avoid common pitfalls like style mismatches, oversized diffs, or missing documentation.
This skill is built for professional developers and AI-assisted workflows alike. It emphasizes transparency by marking AI-generated content and ensuring that all contributions are focused on a single logical change. Whether you are fixing a small typo or proposing a new feature, this skill ensures your work meets the highest standards of the open-source community.
Pull Request Skill Use Cases
- Automating pre-submission checklists to ensure code quality before it reaches maintainers.
- Standardizing pull request descriptions across diverse projects using Openclaw Skills templates.
- Managing AI-assisted code contributions with clear disclosure of testing status and intent.
- Evaluating whether a change requires an upfront issue discussion or can be PRed directly.
- Enforcing rate limits and abandonment prevention to maintain a healthy contributor reputation.
How Pull Request Skill Works
- The skill begins by scanning the repository for a CONTRIBUTING.md file to adapt to the specific project workflow.
- It gathers technical context by checking for configuration files like .editorconfig, prettier, or eslint to match the existing code style.
- The skill evaluates the change scope; if the change is too large or affects sensitive APIs, it prompts for a discussion first.
- It runs a validation check using a internal red-flags.md list to catch common errors or leaked secrets.
- A professional PR description is generated based on predefined templates, explicitly noting the level of testing and AI involvement.
- Once submitted, the skill monitors for feedback, ensuring a response is provided within 48 hours or escalating to a human.
Pull Request Skill Setup
To integrate this skill into your Openclaw Skills environment, ensure your workspace is initialized and follow these steps:
# Install the Pull Request skill
openclaw install pull-request
# Configure your contributor identity
openclaw config set pr.contributor_name "Your Name"
# Initialize the checklist for your current repository
openclaw pull-request --init
Pull Request Skill Data Schema & Taxonomy
The Pull Request skill organizes its logic and validation data through the following schema:
| Component | Purpose |
|---|---|
checklist.md |
A list of mandatory quality checks performed before every submission. |
red-flags.md |
A database of anti-patterns and security risks (like hardcoded secrets) to block. |
repo-context.md |
Stores gathered repository settings, preferred styles, and contribution history. |
templates.md |
Contains various markdown templates for bug fixes, features, and RFCs. |
All AI-assisted PRs are automatically tagged with metadata including untested, lightly tested, or fully tested to ensure full transparency.
Pull Request Skill Advanced Features
- Context-aware issue policy detection that differentiates between small bug fixes and major architecture changes.
- Automated AI disclosure markers added to PR titles and descriptions for ethical Openclaw Skills usage.
- Integrated rate limiting to prevent flooding repositories, enforcing a 24-hour cool-down between submissions.
- Abandonment prevention system that triggers human escalation if review feedback isn't addressed within 48 hours.
- Scope boundary enforcement that stops the process if changes touch more than 5 files or 200 lines of code.
SKILL.md
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