Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Gingiris-1031/gingiris-skills --skill gingiris-github-star-growthgit clone --depth 1 https://github.com/Gingiris-1031/gingiris-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-github-star-growth)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-github-star-growth"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gingiris-github-star-growth/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-github-star-growth"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gingiris-github-star-growth.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00357 | $0.03701 |
| Opus 5.5 | $0.00143 | $0.01480 |
| Sonnet 5.5 | $0.00071 | $0.00740 |
| Haiku 4.5 | $0.00036 | $0.00370 |
Grade A, and why
gingiris-github-star-growth scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 251 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GitHub Star 持续增长实操手册
⚠️ Scope Differentiation:
gingiris-opensource= Launch burst (0→1K in 72h). This skill = Sustained monthly growth (1K→10K→60K+).
2026 执行覆盖条款
先检查 Go / Fix / No-Go：Quick Start 是否由陌生开发者验证、Demo 是否可复现、
License/安全/隐私是否清楚、Issues/PR/社区是否有 owner、是否跟踪 activation/D7/
contributor/qualified lead。No-Go 时停止冲量，先修产品与文档。
统一看板字段：date | source | content URL | spend | repo views | stars | installs | activated | D7 retained | contributors | qualified leads | evidence strength。
2h 只排异常，24h 决定继续/改角度/暂停，72h 选第二波，7d 决定长期复用。
原生数据拿不到写 数据不可用。
禁止买 Star/账号、刷票、激励或协调虚假 Upvote、隐性付费合作、批量抓取并骚扰、 AI 冒充真人互动。平台规则、KOL 报价、账号数据与转化率必须带日期并在执行周复核。
Star 地区分布 & 发布时序（诊断信号，不是 Trending 规则）
适用于 launch 阶段（和
gingiris-opensource配合使用）
- GitHub 未公开“单一国家/地区占比不超过 20%”的 Trending 门槛；只把地域分布 用于判断流量是否匹配目标市场。
- 工具：star-history.com（涨幅趋势）· OSS Insight（国家分布，国人开发）
- 发布时序按 ICP、支持覆盖和时区设计；“首周海外、次周国内”只是一种可测试方案。
- AFFiNE 真实案例：开源第一周拿 6000 star，几乎全来自海外渠道。
- 陪跑好的项目节奏参考：至少提前 2-3 个月准备； 爆发期一周 4000-6000 star，三周可达 10000 star。
Star 地域分布健康基准
AFFiNE 开源前一周研究 VSCode / Vue / AppFlowy 等知名开源项目 star 分布总结的基准（口述回忆，数字加 ≈）
| 地区 | 健康占比 |
|---|---|
| 美国 | ≈19–21% |
| 中国 | ≈19–21% |
| 欧洲（法德意英合计） | ≈10–15% |
| Top 10 常客 | 印度、俄罗斯、巴西通常在列 |
- AFFiNE 的阶段分布属于特定历史案例，使用时标记为口述/项目证据，不外推为算法规则。
- 反模式：为了数字组织与目标用户无关的集中点 Star；它会扭曲市场验证，也可能触发平台风控。
README 用户路径闭环（Star CTA Loop）
AFFiNE 开源实战 SOP：任何用户路径跳出去，都要能跳回来点 star。
- 枚举用户所有出口路径：README→官网；README→开发者文档；README→社区（Discord 等）。
- 每个出口页面都反向链接回 GitHub README：官网、文档站、社区页全部回链。
- 每个回链位置加一句 star CTA（"If you like us, please give us a star on GitHub"）。
- 闭环自检：沿每条路径走一遍，确认用户从任意出口都能一步跳回 repo 并看到 star 引导。
- README/官网随阶段更新：策略目标转变（如转向商业化）就即时改版，不要一成不变。
Star 引流漏斗纪律
- 所有渠道统一回溯 GitHub link，而非官网：Reddit / Twitter / Medium / 目录站发布的链接终点都指向 repo，保证所有流量都会看到 README 里的 star 引导。
- README 30 秒内让用户 get 价值，并直接引导点 star。
- 首周每个渠道发不同主题的 post，不是同一篇复制粘贴。
- 起量第一周每天看 GitHub Insights 的流量来源，据此决定接下来几天重点维护哪些渠道；"维护"= 去该渠道和潜在用户对话，不是 paid marketing。
- 关系型精准触达：只联系公开讨论相关问题或同意接收产品信息的人，逐条个性化， 遵守平台限制并提供退出方式；不要批量抓取竞品 follower 后群发。历史转化数字须标为口述证据。
- 战略转移信号：star 到 ≈6,000 后不再把精力放在 GitHub 本身，转向 1v1 用户聊天 + 搭建用户社区。
- 永远不要买 star：AFFiNE 从未买星，star 涨太快时多家投资人 DD 写爬虫验证 star 来源，完全干净——买星在尽调时必被识破。
- 看增速不看绝对值：star 增速（而非总量）才是融资和 Trending 信号；GitHub Trending 有账号权限体系，非唯 star 论。
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago Changed · +14 lines a50e7a48afa4
- 1mo ago Changed · +15 lines ce05af8dea6e
- 1mo ago First seen · 222 lines · 357 tokens per session scan A b4060a6dbdd4
gingiris-github-star-growth is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (86 stars, last pushed 6d ago), licensed MIT. It adds 357 tokens to every session and 3,701 once invoked, about $0.0014 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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