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研究检索external-servicegithub未标认证来源可访问许可证需确认审计提醒

create-issue创建问题

Agent Skill

用于围绕 GitHub 仓库、Issue、Pull Request、分支、提交和代码协作流程提供辅助能力。它适合让 Agent 查询项目状态、整理变更、辅助创建或检查协作事项,并把仓库中的信息转成可执行的下一步。使用时需要区分只读查询和写入操作;涉及创建 PR、修改 Issue、推送分支或访问私有仓库时,应确认 token 权限、目标仓库范围和用户授权。

总安装

857

周安装

35

GitHub Stars

15

下载量

274
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:create-issue(创建问题)
来源仓库:https://github.com/zxkane/autonomous-dev-team
仓库路径:skills/create-issue
安装命令:
npx skills add https://github.com/zxkane/autonomous-dev-team --skill create-issue
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/zxkane/autonomous-dev-team --skill create-issue

简介

用于围绕 GitHub 仓库、Issue、PR、分支和提交提供协作支持。

  • 可查询项目状态、整理变更、辅助创建事项并生成下一步动作。
  • 适合在开发协作中将信息转化为可执行任务。
  • 涉及写入操作时需确认 token 权限与仓库访问范围。
  • create-issue 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Create GitHub Issue

Create well-structured GitHub issues from user descriptions through interactive clarification.

Repository Detection

Detect the repository from the current git remote:

REPO=$(gh repo view --json nameWithOwner -q '.nameWithOwner')
# Splits into OWNER and REPO_NAME

If detection fails, ask the user for the target repository.

Process

Step 1: Understand the Request

When the user describes a feature or bug, gather context through clarifying questions. Do NOT create the issue immediately.

For features, clarify:

  • What is the user-facing goal? (not implementation details)
  • What are the acceptance criteria? (how to verify it works)
  • Are there UI/UX implications?
  • What existing functionality does this relate to?
  • Priority and scope constraints

For bugs, clarify:

  • Steps to reproduce
  • Expected vs actual behavior
  • Environment (prod, staging, PR preview)
  • Severity (blocking, degraded, cosmetic)
  • Any error messages or logs

Ask 2-3 focused questions per round. Stop when there is enough information to write a clear issue.

Step 2: Draft the Issue

Use the appropriate template based on issue type. For full template content, consult references/issue-templates.md.

Both templates include these required sections:

  • Summary / Motivation (feature) or Steps to Reproduce (bug)
  • Requirements with checkboxes (feature) or Expected/Actual Behavior (bug)
  • Testing Requirements (mandatory TDD section: test cases doc, unit tests, E2E tests)
  • Acceptance Criteria with checkboxes
  • Dependencies section for issue ordering

Step 2.5: Detect & Attach Workspace Changes

After drafting the issue, check the workspace for local changes that may provide useful context for the autonomous dev agent. For the complete detection, attachment, and cleanup procedure, consult references/workspace-changes.md.

Summary:

  1. Run git status --short — skip if no changes
  2. Summarize changes and ask user for confirmation
  3. Choose strategy based on diff size: inline (< 500 lines), branch push (>= 500 lines), or file list fallback
  4. Add a ## Pre-existing Changes section to the issue body
  5. Optionally clean up local changes after attachment

Step 3: Confirm with User

Present the draft issue to the user with:

  1. Proposed title (concise, descriptive)
  2. Full issue body (including Pre-existing Changes section if applicable)
  3. Proposed labels
  4. Whether to add autonomous label

Use AskUserQuestion to confirm:

  • "Does this issue look correct? Should I create it?"
  • Ask about autonomous label: whether AI should handle this automatically

Step 4: Create the Issue

Use GitHub MCP tools or gh CLI to create the issue with:

  • title: The confirmed title
  • body: The confirmed body
  • labels: Appropriate labels (see Label Guide below)

Report the created issue URL to the user.

If branch push was deferred (large diff strategy):

After the issue is created and the issue number is known:

  1. Execute the branch push commands from Step 2.5.5 using the actual issue number
  2. Update the issue body to include the branch reference section

Label Guide

LabelWhen to Apply
bugBug reports
enhancementFeature requests
autonomousUser confirms AI should handle dev/test/review/merge automatically
no-auto-closeUsed with autonomous -- AI handles dev/test/review but stops before merge, requiring manual approval
documentationDocumentation-only changes
good first issueSimple, well-scoped tasks

Autonomous Label Decision

After drafting the issue, explicitly ask the user whether to add the autonomous label.

Provide guidance on when autonomous is appropriate:

  • Good fit: Well-defined scope, clear acceptance criteria, follows existing patterns, no ambiguous design decisions
  • Poor fit: Requires significant architecture decisions, needs user input during development, involves sensitive infrastructure changes, exploratory/research tasks

Frame the question as:

"Should this issue be handled by the autonomous development pipeline? The AI will automatically develop, test, review, and merge the changes. This works best for well-defined tasks with clear acceptance criteria."

If the user selects autonomous, also ask about no-auto-close:

"Should this issue also have the no-auto-close label? With this label, the AI will handle development, testing, and review, but will stop before merging -- you'll be notified to make the final merge decision. This is recommended for sensitive infrastructure changes, features needing product sign-off, or experimental work."

Label interaction summary:

  • autonomous alone = AI handles dev/test/review and auto-merges on pass
  • autonomous + no-auto-close = AI handles dev/test/review but stops before merge, notifying the owner for manual approval

Writing Guidelines

  • Title: Start with verb, be specific. "Add pagination to plans list page" not "Plans page improvement"
  • Body: Write for an AI developer who has access to the full codebase but no verbal context from this conversation
  • Acceptance criteria: Must be objectively verifiable, not subjective
  • Scope: Prefer smaller, focused issues over large multi-part ones
  • References: Link to related issues, PRD sections, or code paths when relevant
  • Dependencies: When creating multiple related issues, populate the ## Dependencies section with links to blocking issues. Create issues in dependency order so earlier issue numbers are available for later ones. The dispatcher will skip issues whose dependencies are still open.
  • Testing Requirements: ALWAYS include the "Testing Requirements" section. The dev agent follows the project's TDD workflow but has been observed to skip E2E tests or test-case docs when the issue doesn't explicitly call them out. Be specific about:

- Key scenarios each test type must cover (2-4 bullet points) - For bugs: the regression test must fail before the fix and pass after

Multi-Issue Creation

When breaking a large feature into multiple issues:

  1. Create issues in dependency order — issues with no dependencies first, then issues that depend on them. This ensures issue numbers are known when writing dependency references.
  2. Populate the ## Dependencies section in each issue body with #N links to blocking issues.
  3. Use a consistent naming scheme — prefix titles with the project/feature name for easy filtering (e.g., "MyProject: Add DynamoDB infrastructure").
  4. Cross-reference the plan — if an implementation plan exists, link each issue to the relevant plan tasks/chunks.
  5. The dispatcher skips blocked issues — issues with open dependencies in the ## Dependencies section are ignored by the autonomous dispatcher until all dependencies are resolved (closed/merged).

References

For detailed content, consult:

  • references/issue-templates.md -- Full feature and bug issue templates with all required sections
  • references/workspace-changes.md -- Complete workspace change detection, attachment strategies, and cleanup procedure

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.9%
按下载量换算104

Claude

29.9%
按下载量换算82

Cursor

17.64%
按下载量换算48

Gemini CLI

10.67%
按下载量换算29

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

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来源信息

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