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issue-hunter

Analyze, triage, and select the best issues to work on from GitHub repositories. Scores issues by reproducibility, scope, complexity, and community signal. Produces a structured analysis document with root cause hypotheses and fix approaches. Use when deciding which issues to tackle in open-source projects, prioritizing a backlog, or analyzing bug reports.

作者: admin | 来源: ClawHub
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ClawHub
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V 1.0.0
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issue-hunter

# Issue Hunter — Issue Analysis & Selection ## Overview Systematically analyze open issues in target repositories, score them by fixability, and select the best candidates to work on. Produces a structured analysis document with root cause hypotheses and fix approaches. **Use cases**: Open-source contribution targeting, sprint planning, backlog grooming, bug triage. ## Prerequisites GitHub CLI must be authenticated — issue fetching relies on `gh` API calls: ```bash gh auth status # Must show "Logged in" ``` If not configured, ask the user to provide: 1. **GitHub username** 2. **GitHub token** — run `gh auth login` or set `export GH_TOKEN=<token>` Without auth, API rate limits will block bulk issue fetching. ## Workflow ### Step 1: Fetch Issues For each target repository, fetch open issues: ```bash # Fetch bug-labeled issues gh issue list --repo {owner}/{repo} --label bug --state open --limit 30 \ --json number,title,body,labels,comments,createdAt,updatedAt # Also check these labels gh issue list --repo {owner}/{repo} --label "good first issue" --state open --limit 10 \ --json number,title,body,labels,comments,createdAt gh issue list --repo {owner}/{repo} --label "help wanted" --state open --limit 10 \ --json number,title,body,labels,comments,createdAt ``` If no label filtering works, fetch recent open issues: ```bash gh issue list --repo {owner}/{repo} --state open --limit 50 \ --json number,title,body,labels,comments,createdAt ``` ### Step 2: Score Each Issue Rate each issue on these factors: | Factor | 3 (High) | 2 (Medium) | 1 (Low) | |--------|----------|-----------|---------| | **Reproducibility** | Clear repro steps, stack trace | Partial description | Vague "doesn't work" | | **Scope** | Single module/file | 2-3 files | Cross-cutting concern | | **Complexity** | Logic bug, missing check | Algorithm issue | Architecture redesign | | **Community signal** | Multiple reports, 👍 | Some engagement | Single report, no reaction | | **Freshness** | Recent, no PR attempts | Moderate age | Old, multiple failed PRs | | **Testability** | Can write automated test | Partially testable | Manual testing only | **Total score** = sum of all factors (max 18). ### Step 3: Select Candidates **Selection criteria** (in priority order): 1. Clearly a bug (not a feature request in disguise) 2. Self-contained (fixable without deep domain knowledge) 3. Testable (can write automated tests to verify) 4. No existing PR addressing it 5. Score ≥ 12/18 **Red flags** — skip issues if: - Already has an open PR (check with `gh pr list --repo owner/repo --search "fixes #{number}"`) - Requires access to proprietary services/APIs - Involves native/platform-specific code you can't test - Maintainer has said "won't fix" or "by design" ### Step 4: Deep-Dive Selected Issues For each selected issue: 1. **Read the full thread** — comments often contain root cause hints or partial fixes 2. **Identify relevant source files** — search the codebase for keywords from the issue 3. **Draft a root cause hypothesis** — "I believe X happens because Y" 4. **Draft a fix approach** — "I'll modify Z to handle the W case" 5. **Estimate effort** — Low (< 1 hour), Medium (1-4 hours), High (4+ hours) ### Step 5: Produce Analysis Document Write `{workspace}/issue-analysis.md`: ```markdown # Issue Analysis — {Repository/Campaign Name} > Generated: {date} ## Summary | # | Repository | Issue | Title | Score | Effort | Status | |---|-----------|-------|-------|-------|--------|--------| | 1 | owner/repo | #123 | Bug title | 16/18 | Low | Selected | | 2 | owner/repo | #456 | Bug title | 12/18 | Medium | Selected | | 3 | owner/repo | #789 | Bug title | 8/18 | High | Skipped | --- ## Detailed Analysis ### owner/repo — Selected: #123 — Bug title - **Score**: 16/18 (Repro: 3, Scope: 3, Complexity: 3, Signal: 2, Fresh: 3, Testable: 2) - **Root cause**: {hypothesis} - **Fix approach**: {description} - **Files to modify**: `path/to/file.py`, `tests/test_file.py` - **Effort estimate**: Low (< 1 hour) - **Risk**: Low — straightforward null check - **Dependencies**: None ### owner/repo — Skipped: #789 — Bug title - **Reason**: Requires architecture redesign, score 8/18 ``` ## Output - `{workspace}/issue-analysis.md` — Per-repo issue analysis with selections ## Tips - Pairs naturally with **repo-scout** (upstream) and **repo-setup** / **dev-test** (downstream). - For sprint planning: use the scoring system on your own project's issues to prioritize. - For backlog grooming: run periodically to re-score issues as new information appears. - When analyzing a single repo, skip the summary table and go straight to detailed analysis.

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skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

方式一:安装 SkillHub 和技能

帮我安装 SkillHub 和 issue-hunter-1776050410 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 issue-hunter-1776050410 技能

通过命令行安装

skillhub install issue-hunter-1776050410

下载 Zip 包

⬇ 下载 issue-hunter v1.0.0

文件大小: 2.88 KB | 发布时间: 2026-4-14 10:07

v1.0.0 最新 2026-4-14 10:07
- Initial release of issue-hunter skill.
- Analyze, triage, and prioritize GitHub issues using a structured, multi-factor scoring system (reproducibility, scope, complexity, community signal, freshness, testability).
- Fetches and filters issues from GitHub repositories via `gh` CLI (requires authentication).
- Generates an analysis document with root cause hypotheses and proposed fix approaches for selected issues.
- Supports use cases including open-source contribution targeting, sprint planning, backlog grooming, and bug triage.

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