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zammad-mcp-quality

Automate pre-PR quality checks for Zammad MCP contributions.

37|25|Updated Jul 6, 2025
Search Tags:#code quality#automation#development#code review#MCP#Zammad#CodeRabbit
One-click install
npx skills add https://github.com/basher83/Zammad-MCP --skill zammad-mcp-quality
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: zammad-mcp-quality
Source: https://github.com/basher83/Zammad-MCP/tree/main/.claude/skills/zammad-mcp-quality
Command: npx skills add https://github.com/basher83/Zammad-MCP --skill zammad-mcp-quality

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pytest, ruff, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill addresses the challenges of inconsistent code quality, recurring CodeRabbit feedback, and slow PR review cycles in Zammad MCP development. It provides a structured system to ensure high-quality contributions and continuous learning.

Core Features & Use Cases

  • Pre-PR Self-Review: Utilize the pre-pr-checklist.md to proactively identify and fix common issues before creating a Pull Request, significantly reducing review iterations.
  • Pattern Learning & Guidance: Access consolidated CodeRabbit feedback in coderabbit-learnings.md and detailed guides (e.g., pagination-patterns.md, error-handling-guide.md) to understand and prevent recurring mistakes.
  • Systematic Improvement: Integrates a feedback loop to continuously update quality standards and documentation, fostering a self-improving development process.
  • Use Case: Before submitting a new feature for Zammad MCP, use this Skill to run through a comprehensive checklist and review common pitfalls, ensuring your code meets project standards and passes review quickly.

Quick Start

Run pre-PR quality checks from your project root

./scripts/quality-check.sh && uv run pytest --cov=mcp_zammad

Frequently Asked Questions about zammad-mcp-quality

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate code quality checks for Zammad MCP development?▼

Automate code quality checks by running the pre-PR quality script from your project root: `./scripts/quality-check.sh && uv run pytest --cov=mcp_zammad`. This enforces type annotations, error messages, pagination metadata, docstrings, and runs pytest with coverage to catch issues before PR submission.

What does a pre-PR checklist help prevent in code review?▼

A pre-PR checklist proactively identifies and fixes common issues—actionable error messages, correct pagination metadata, Python 3.10+ type annotations, and comprehensive docstrings—before submission, significantly reducing CodeRabbit feedback cycles and review iterations.

Can I use ruff and pytest to enforce coding patterns in my MCP contributions?▼

Yes. Ruff and pytest are built-in dependencies that enforce Python coding patterns and run comprehensive test coverage. The quality-check script integrates both to validate that your contributions meet Zammad MCP standards for type safety, formatting, and test coverage.

How do I handle recurring CodeRabbit feedback on pagination and error handling?▼

Reference consolidated CodeRabbit feedback and detailed guides in `coderabbit-learnings.md`, `pagination-patterns.md`, and `error-handling-guide.md`. These document common patterns and mistakes, enabling you to learn from past reviews and prevent recurrence in new contributions.

When should I run quality checks during MCP tool development?▼

Run quality checks before creating PRs, during MCP tool development, when adding pagination, handling errors, onboarding new contributors, and in monthly maintainer reviews. This ensures consistent code quality and continuous learning across the development lifecycle.

What's the difference between running checks locally vs. during code review?▼

Running checks locally with the pre-PR script catches issues early—type mismatches, missing docstrings, pagination errors—before submission. This self-review loop reduces review cycles by addressing problems proactively, making the formal code review faster and more focused.

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