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github-issue-resolverGitHub issue resolver 搜索

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

50,780

周安装

2,159

GitHub Stars

1

下载量

17,790
OpenClaw

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

MIT-0

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:github-issue-resolver(GitHub issue resolver 搜索)
来源仓库:https://github.com/ashwinhegde19/github-issue-resolver
安装命令:
openclaw skills install github-issue-resolver
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install github-issue-resolver

简介

用于自治式解决 GitHub 存储库中的未解决问题。

  • 适合发现、分析并修复 open issues。
  • 通过 clawhub 安装后,由“resolve issue”类指令触发。
  • 需 issue 读写权限和充分上下文理解能力。
  • 存在护栏机制防止误操作,但仍需人工监督。github-issue-resolver 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
github-issue-resolver
description
Autonomous GitHub Issue Resolver Agent with guardrails. Use when the user wants to discover, analyze, and fix open issues in GitHub repositories. Triggers on requests like "fix GitHub issues", "resolve issues in repo", "work on GitHub bugs", or when the user provides a GitHub repository URL and asks for issue resolution. Supports the full workflow from issue discovery to PR submission with safety guardrails preventing scope creep, unauthorized access, and dangerous operations.

GitHub Issue Resolver

Autonomous agent for discovering, analyzing, and fixing open GitHub issues — with a 5-layer guardrail system.

⚠️ GUARDRAILS — Read First

Every action goes through guardrails. Before any operation:

  1. Load guardrails.json config
  2. Validate scope (repo, branch, path)
  3. Check action gate (auto/notify/approve)
  4. Validate command against allowlist
  5. Log to audit trail

For guardrail details, see references/guardrails-guide.md.

Key Rules (Non-Negotiable)

  • Never touch protected branches (main, master, production)
  • Never modify .env, secrets, CI configs, credentials
  • Never force push
  • Never modify dependency files without explicit approval
  • Never modify own skill/plugin files
  • One issue at a time — finish or abandon before starting new
  • All dangerous actions require user approval (write code, commit, push, PR)
  • Everything is logged to audit/ directory

Workflow

Phase 1 — Issue Discovery

Trigger: User provides a GitHub repository (owner/repo).

Steps:

  1. Validate repo against guardrails:
   python3 scripts/guardrails.py repo <owner> <repo>

If blocked, tell the user and stop.

  1. Fetch, score, and present issues using the recommendation engine:
   python3 scripts/recommend.py <owner> <repo>

This automatically fetches open issues, filters out PRs, scores them by severity/impact/effort/freshness, and presents a formatted recommendation.

Always use recommend.py — never manually format issue output. The script ensures consistent presentation every time.

For raw JSON (e.g., for further processing):

   python3 scripts/recommend.py <owner> <repo> --json

⏹️ STOP. Wait for user to select an issue.


Phase 2 — Fixing

Trigger: User selects an issue.

Steps:

  1. Lock the issue (one-at-a-time enforcement):
   python3 scripts/guardrails.py issue_lock <owner> <repo> <issue_number>
  1. Read full issue thread including comments.
  1. Clone the repo (Gate: notify):
   python3 scripts/sandbox.py run git clone https://github.com/<owner>/<repo>.git /tmp/openclaw-work/<repo>
  1. Create a safe branch (Gate: auto):
   python3 scripts/sandbox.py run git checkout -b fix-issue-<number>
  1. Explore codebase — read relevant files. For each file:
   python3 scripts/guardrails.py path <file_path>
  1. Plan the fix — explain approach to user:
   ## Proposed Fix
   - Problem: [root cause]
   - Solution: [what changes]
   - Files: [list of files and what changes in each]
   - Estimated diff size: [lines]

⏹️ STOP. Wait for user to approve the plan before implementing.

  1. Implement the fix (Gate: approve):

- Apply changes - Check diff size: python3 scripts/guardrails.py diff <line_count> - Log: python3 scripts/audit.py log_action write_code success


Phase 3 — Testing

After implementing:

  1. Find and run tests (Gate: notify):
   python3 scripts/sandbox.py run npm test   # or pytest, cargo test, etc.
  1. If tests fail AND autoRollbackOnTestFail is true:

- Revert all changes - Notify user - Suggest alternative approach

  1. If no tests exist, write basic tests covering the fix.
  1. Report results to user.

Phase 4 — Draft PR for Review (Approval REQUIRED)

⚠️ NEVER create PR automatically. Always ask first.

Do NOT dump full diffs in chat. For any non-trivial project, push the branch and let the user review on GitHub where they get syntax highlighting, file-by-file navigation, and inline comments.

  1. Commit changes (Gate: approve):
   python3 scripts/sandbox.py run git add .
   python3 scripts/sandbox.py run git commit -m "Fix #<number>: <title>"
  1. Show a change summary (NOT the raw diff) — keep it concise:
   ## Changes
   - **src/models.py** — Added field validation (title length, enum checks)
   - **app.py** — Added validation to POST endpoint, 400 error responses
   - **tests/test_app.py** — 22 new tests covering validation rules
   - 4 files changed, ~100 lines of source + ~150 lines of tests
   - All tests passing ✅
  1. Ask explicitly: "Ready to push and create a draft PR?"
  1. Only after user says "yes" (Gate: approve):
   python3 scripts/sandbox.py run git push -u origin fix-issue-<number>
   python3 scripts/sandbox.py run gh pr create --draft --title "..." --body "..."

Note: PRs are always created as draft by default. The PR body should include a detailed description of all changes, test results, and link to the issue (Closes #N).

  1. Share the PR link — user reviews on GitHub.
  1. Unlock the issue:
   python3 scripts/guardrails.py issue_unlock

Scripts Reference

ScriptPurposeRun Without Reading
scripts/recommend.pyPrimary entry point — fetch, score, and present issues
scripts/fetch_issues.pyRaw issue fetcher (used internally by recommend.py)
scripts/analyze_issue.pyDeep analysis of single issue
scripts/create_pr.pyPR creation wrapper
scripts/guardrails.pyGuardrail enforcement engine
scripts/sandbox.pySafe command execution wrapper
scripts/audit.pyAction logger

References

适合场景

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能力概览

能力 1

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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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

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按下载量换算14,782

安全审计

VirusTotal

通过

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通过

Static analysis

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

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