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/github-demand-radar

Use when the user asks to analyze a GitHub repository's issues/PRs to identify high-value commercial demand opportunities. Triggers: 「扫issue」「扫PR」「找需求」「分析仓库」「找商业化点子」「独立开发者切入点」「需求雷达」「扫一下明星项目」「生成需求报告」. Outputs scored demand cards with JTBD analysis, RICE scoring, Ugly Workaround

From plugin
github-demand-radar
161 skill
Install
$ npx -y skills add geekjourneyx/github-demand-radar --skill github-demand-radar --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/github-demand-radar

Context preview

The summary Claude sees to decide when to auto-load this skill.

Use when the user asks to analyze a GitHub repository's issues/PRs to identify high-value commercial demand opportunities. Triggers: 「扫issue」「扫PR」「找需求」「分析仓库」「找商业化点子」「独立开发者切入点」「需求雷达」「扫一下明星项目」「生成需求报告」. Outputs scored demand cards with JTBD analysis, RICE scoring, Ugly Workaround

SKILL.md

github-demand-radar.SKILL.md
name: github-demand-radar
description: "Use when the user asks to analyze a GitHub repository's issues/PRs to identify high-value commercial demand opportunities. Triggers: 「扫issue」「扫PR」「找需求」「分析仓库」「找商业化点子」「独立开发者切入点」「需求雷达」「扫一下明星项目」「生成需求报告」. Outputs scored demand cards with JTBD analysis, RICE scoring, Ugly Workaround evidence, and fake-door probe drafts. Also works in PR scan mode (Phase 1B) to find rejected/stale PRs as market gap signals."
dependencies: gh, jq

GitHub 需求雷达

🎯 核心目标

你是一个顶级的**技术商业化产品专家**。当用户要求分析某个 GitHub 仓库时,你的任务不是总结 issue,而是**穿透噪音,找到具备独立商业化潜力、存在生态位空缺的真需求**,并生成可立即用于 fake door 验证的探针草稿。

🚦 触发条件

  • 「分析 / 扫描 [仓库名] 的需求 / issue」→ **Issue 扫描模式**(Phase 1 → Phase 4)
  • 「扫 PR / 扫描 PR / PR 扫描 / 分析 [仓库名] 的 PR」→ **PR 扫描模式**(Phase 1B → Phase 4)
  • 「找商业化点子 / 独立开发者切入点 / 选题」
  • 「扫一下明星项目」→ 加载 `references/starred-repos.md`,依次分析
  • 「找跨生态共振需求」→ 直接跳到 **Phase 5 生态雷达**,不抓新数据
  • 「这个开源项目有什么值得做的周边工具」
  • 「生成报告」→ 跳到 **Phase 4B/4C**,使用本次会话已完成的评审结果写入文件(仅在已完成 Phase 3 后可用)

🚫 硬性约束(任何时候都不得违反)

1. **绝不全量读取 issue/PR**:所有 `gh issue view`/`gh pr view` 调用必须带 `--jq` 截断,绝不输出原始全文 2. **绝不省略探针草稿**:RICE ≥ 50 的需求必须写入 `probes/` 文件,不可只输出报告 3. **绝不臆造数据**:所有 RICE 分数必须来自真实抓到的 reactions/comments 数值 4. **Token 安全阀**:候选超过 10 个时,先按 reactions 排序取 Top 10 进入深析 5. **巨无霸项目软警告**:Stars > 100k 的项目先输出:「⚠️ 该项目生态位已固化(stars > 100k),独立开发者切入空间有限。是否仍要继续?」等待确认后再继续 6. **PR 扫描专属**:类型 B(Closed+Unmerged)的 PR 即使无 bug 关键词也必须进入评审,这是最强的市场空白信号;参考 `references/pr-scan-guide.md`

---

🔄 核心工作流

Phase 0 — 历史注入(可选,仅当 reports/_index.jsonl 存在时执行)

# 检查历史索引是否存在
ls reports/_index.jsonl 2>/dev/null && \
  cat reports/_index.jsonl | \
  python3 -c "
import sys, json
from datetime import datetime, timedelta
cutoff = (datetime.now() - timedelta(days=30)).isoformat()[:10]
for line in sys.stdin:
    d = json.loads(line)
    if d.get('viability') == 'HIGH' and d.get('date','') >= cutoff:
        print(json.dumps({'job_x': d['job_x'], 'repo': d['repo'], 'rice': d['rice'], 'tags': d.get('tags',[])}))
" 2>/dev/null || echo "(无历史数据,跳过 Phase 0)"

将输出的历史 HIGH 需求摘要注入 Phase 3 评估上下文。若某 job_x 在历史中出现 ≥ 2 次,在评估时将 RICE 的 Reach 维度设为 10(跨生态共振信号)。

---

Phase 1 — 数据摄取与硬过滤(零 LLM,纯命令行)

**步骤 0(前置检查)**:运行以下两条验证,任一失败则终止并提示用户:

# 检查 gh 认证
gh auth status 2>&1 | grep -q "Logged in" || \
  echo "❌ 未登录 GitHub,请先执行: gh auth login" && exit 1

# 检查仓库是否存在
gh repo view <owner>/<repo> --json name 2>&1 | grep -q '"name"' || \
  echo "❌ 仓库 <owner>/<repo> 不存在或无访问权限,请确认拼写" && exit 1

**步骤 1**:确定目标仓库和时间窗口(默认 30 天,用户可指定)

**步骤 2**:用 GitHub Search API 拉取数据(唯一可靠获取 reactions 数量的方式)

# macOS
SINCE=$(date -v-30d +%Y-%m-%d)
# Linux
# SINCE=$(date -d '30 days ago' +%Y-%m-%d)

GH_PAGER="" gh api \
  "search/issues?q=repo:<owner>/<repo>+is:issue+is:open+created:>=${SINCE}-label:bug-label:invalid-label:duplicate-label:wontfix&sort=reactions&order=desc&per_page=100" \
  --jq '[.items[] | {
    number: .number,
    title:  .title,
    reactions: .reactions.total_count,
    comments:  .comments,
    labels:    [.labels[].name],
    created:   .created_at[:10],
    url:       .html_url
  }]'

**步骤 3**:用 jq 过滤低信噪比 issue,只保留满足以下任一条件的:

  • reactions ≥ 5,或
  • comments ≥ 5,或
  • 标题包含 feature/support/integrate/request(忽略大小写)
# 继续管道
| jq '[.[] | select(
    .reactions >= 5
    or .comments >= 5
    or (.title | test("(?i)feature|support|integrat|request"))
)]'

**步骤 4(可选)**:补充拉取高 reactions 的已关闭 issue(可能有未解决的强需求)

GH_PAGER="" gh api \
  "search/issues?q=repo:<owner>/<repo>+is:issue+is:closed+created:>=${SINCE}&sort=reactions&order=desc&per_page=30" \
  --jq '[.items[] | select(.reactions.total_count >= 10) |
    {number:.number, title:.title, reactions:.reactions.total_count,
     comments:.comments, state:"closed", created:.created_at[:10]}]'

记录候选数量,确保不超过 10 个进入 Phase 2(超过则取 reactions 最高的 10 个)。

> ⚠️ API 限流提示:Search API 限制 30次/分钟(认证用户)。若遇到 403/429,等待 60 秒后重试。

**零结果 Fallback**:若 Phase 1 候选数量为 0,按以下顺序尝试放宽: 1. 去掉 label 过滤(保留 bug 类 issue) 2. 将时间窗口扩大到 90 天 3. 若仍为空,输出:「⚠️ 该仓库近期 issue 活跃度不足,建议扫描 `references/starred-repos.md` 中的高活跃仓库。」并终止

---

Phase 1B — PR 扫描数据摄取(仅在 PR 扫描模式下执行,替代 Phase 1)

> 参考:`references/pr-scan-guide.md`

**入口确认**:进入 PR 扫描前,先向用户确认:

🔍 PR 扫描模式
  仓库: <owner>/<repo>
  时间窗口: 90 天(含三类信号: Open / Rejected / Stale)
  预计 API 调用: 3 次
确认开始?[Y/n]

确认后继续;用户取消则退出并说明可改用 Issue 扫描模式。

PR 扫描默认窗口为 **90 天**(PR 积累时间比 issue 长)。分三类并行拉取:

**类型 A:高关注开放 PR**

SINCE=$(date -v-90d +%Y-%m-%d)   # macOS;Linux: date -d '90 days ago' +%Y-%m-%d
gh api "search/issues?q=repo:<owner>/<repo>+is:pr+is:open+created:>=${SINCE}&sort=reactions&order=desc&per_page=30" \
  --jq '.items[] | {number:.number, title:.title, reactions:.reactions.total_count,
    comments:.comments, pr_type:"A-open", state:"open", created:.created_at[:10],
    labels:[.labels[].name]}'

**类型 B:被拒绝 PR(Closed + Unmerged)⭐ 最强商业信号**

gh api "search/issues?q=repo:<owner>/<repo>+is:pr+is:closed+is:unmerged+created:>=${SINCE}&sort=reactions&order=desc&per_page=30" \
  --jq '.items[] | {number:.number, title:.title, reactions:.reactions.total_count,
    comments:.comments, pr_type:"B-rejected", state:"rejected", created:.created_at[:10],
    labels:[.labels[].name]}'

**类型 C:长期 Stale PR(超过 180 天未更新的 Open PR)**

STALE_BEFORE=$(date -v-180d +%Y-%m-%d)   # macOS;Linux: date -d '180 days ago' +%Y-%m-%d
gh api "search/issues?q=repo:<owner>/<repo>+is:pr+is:open+updated:<${STALE_BEFORE}&sort=reactions&order=desc&per_page=20" \
  --jq '.items[] | {number:.number, title:.title, reactions:.reactions.total_count,
    comments:.comments, pr_type:"C-stale", state:"stale", created:.created_at[:10],
    labels:[.labels[].name]}'

**合并去重**:三类结果合并后按 `reactions + comments` 排序,去掉重复 number,取 Top 10 进入 Phase 2。

Bouncer 硬性过滤(在进入 Phase 3 前先用 jq 清洗):

  • `pr_type` 非 B-rejected 且标题含 `fix|bug|typo|chore|docs|readme|revert|bump|ci:|test:` → 排除(除非 reactions ≥ 20)
  • labels 含 `duplicate` → 排除
  • author 含 `bot`/`dependabot` → 排除
  • **类型 B 任何 reactions ≥ 10 的 PR 必须保留**,不受关键词过滤影响

RICE 评分

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Ships withgithub-demand-radar

从 GitHub issues 和 PR 中发现可商业化产品机会的 Agent Skill。

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16
Stars
4
Forks
Maintained
Maintenance
MIT
License
3mo ago
Last commit
4mo ago
Created

Repo: geekjourneyx/github-demand-radar