跳到正文
FunCoding

搜索

搜索文档、Skill 和 MCP

describe-pr

Generate comprehensive PR descriptions following repository templates

AI 与智能体3.9k.claude/skills/describe_pr/SKILL.md

安装

把这段话发给 Claude Code、Codex 或 Cursor。智能体会先检查安全性,你确认后才安装。

读取 https://funcoding.ai/skills/parcadei/continuous-claude-v3/describe-pr/install.md ,按里面的步骤帮我安装这个 Skill。

SKILL.md

Generate PR Description

You are tasked with generating a comprehensive pull request description following the repository's standard template.

Steps to follow:

  1. Read the PR description template:

    • First, check if thoughts/shared/pr_description.md exists
    • If it doesn't exist, inform the user they need to create a PR description template at thoughts/shared/pr_description.md
    • Read the template carefully to understand all sections and requirements
  2. Identify the PR to describe:

    • Check if the current branch has an associated PR: gh pr view --json url,number,title,state 2>/dev/null
    • If no PR exists for the current branch, or if on main/master, list open PRs: gh pr list --limit 10 --json number,title,headRefName,author
    • Ask the user which PR they want to describe
  3. Check for existing description:

    • Check if thoughts/shared/prs/{number}_description.md already exists
    • If it exists, read it and inform the user you'll be updating it
    • Consider what has changed since the last description was written
  4. Gather comprehensive PR information:

    • Get the full PR diff: gh pr diff {number}
    • If you get an error about no default remote repository, instruct the user to run gh repo set-default and select the appropriate repository
    • Get commit history: gh pr view {number} --json commits
    • Review the base branch: gh pr view {number} --json baseRefName
    • Get PR metadata: gh pr view {number} --json url,title,number,state

4b. Gather reasoning history (if available):

  • Check if reasoning files exist: ls .git/claude/commits/*/reasoning.md 2>/dev/null
  • If they exist, aggregate them: bash "$CLAUDE_PROJECT_DIR/.claude/scripts/aggregate-reasoning.sh" main
  • This shows what approaches were tried before the final solution
  • Save the output for inclusion in the PR description
  1. Analyze the changes thoroughly: (ultrathink about the code changes, their architectural implications, and potential impacts)

    • Read through the entire diff carefully
    • For context, read any files that are referenced but not shown in the diff
    • Understand the purpose and impact of each change
    • Identify user-facing changes vs internal implementation details
    • Look for breaking changes or migration requirements
  2. Handle verification requirements:

    • Look for any checklist items in the "How to verify it" section of the template
    • For each verification step:
      • If it's a command you can run (like make check test, npm test, etc.), run it
      • If it passes, mark the checkbox as checked: - [x]
      • If it fails, keep it unchecked and note what failed: - [ ] with explanation
      • If it requires manual testing (UI interactions, external services), leave unchecked and note for user
    • Document any verification steps you couldn't complete
  3. Generate the description:

    • Fill out each section from the template thoroughly:
      • Answer each question/section based on your analysis
      • Be specific about problems solved and changes made
      • Focus on user impact where relevant
      • Include technical details in appropriate sections
      • Write a concise changelog entry
    • If reasoning files were found (from step 4b):
      • Add an "## Approaches Tried" section before "## How to verify it"
      • Include the aggregated reasoning showing failed attempts and what was learned
      • This helps reviewers understand the journey, not just the destination
    • Ensure all checklist items are addressed (checked or explained)
  4. Save the description:

    • Write the completed description to thoughts/shared/prs/{number}_description.md
    • Show the user the generated description
  5. Update the PR:

    • Update the PR description directly: gh pr edit {number} --body-file thoughts/shared/prs/{number}_description.md
    • Confirm the update was successful
    • If any verification steps remain unchecked, remind the user to complete them before merging

Important notes:

  • This command works across different repositories - always read the local template
  • Be thorough but concise - descriptions should be scannable
  • Focus on the "why" as much as the "what"
  • Include any breaking changes or migration notes prominently
  • If the PR touches multiple components, organize the description accordingly
  • Always attempt to run verification commands when possible
  • Clearly communicate which verification steps need manual testing

相似的 Skill

brand-guidelines
anthropics/skills180k

brand-guidelines

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

AI 与智能体

internal-comms
anthropics/skills180k

internal-comms

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

AI 与智能体

template-skill
anthropics/skills180k

template-skill

Replace with description of the skill and when Claude should use it.

AI 与智能体

mcp-builder
anthropics/skills180k

mcp-builder

Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

AI 与智能体

algorithmic-art
anthropics/skills180k

algorithmic-art

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

AI 与智能体

academy-guide
anthropics/skills180k

academy-guide

Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.

AI 与智能体