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 gr-oss-marketinggit 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/gr-oss-marketing)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gr-oss-marketing"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gr-oss-marketing/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/gr-oss-marketing"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gr-oss-marketing.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 | $0.00097 | $0.01337 |
| Opus 5 | $0.00048 | $0.00668 |
| Sonnet 5 | $0.00019 | $0.00267 |
| Haiku 4.5 | $0.00010 | $0.00134 |
Grade A, and why
gr-oss-marketing 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 12d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gr-oss-marketing — 开源营销
什么时候用
- "我要发一个开源项目，从 0 怎么起"
- "GitHub star 增长卡在 xxx 不动了"
- "如何找开发者 KOL 合作"
- "Reddit / HN 怎么发不被 ban"
- "如何做 dev.to / Zenn / CSDN 内容矩阵"
核心框架（3 阶段）
阶段 1：Pre-launch（T-30 到 T-0）
- README 起好（英文主，首屏截图 < 3s 读懂）
- Demo video ≤ 60s，有字幕
- License 选对（MIT/Apache-2/AGPL 各有陷阱）
- 3-5 个早鸟 maintainer / contributor
- 社群频道就位（Discord 或 Telegram，英文为主）
阶段 2：Launch（T-0 到 T+14）
- Product Hunt 发（联动
gr-ph-launch） - Hacker News Show HN（周二美东 9am 或周六）
- Reddit：选 3 个相关 sub（r/selfhosted / r/programming / 细分技术 sub）
- Dev.to / Zenn / CSDN 发技术深度文
- 找 3-5 个 KOL 转（优先活跃度 > follower 数）
阶段 3：Growth（T+14 到 T+180）
- 每周 1 篇技术 blog（联动
gr-blog-post） - GitHub Issues → 内容素材（用户问题变 FAQ）
- 每月发 1 次 update（邮件列表 + Discord）
- 出海本地化（日韩先，联动 gr-blog-post i18n 流程）
深度参考
所有细节、KOL 清单、话术模板、案例库在 upstream repo：
📂 https://skills.sh/Gingiris-1031
references/preparation.md— Pre-launch 完整清单references/channels.md— 分发渠道矩阵references/templates.md— KOL 接触话术 / Reddit 模板 / HN Show HN 模板references/seo-geo-guide.md— 开源项目 SEO/GEO
首次调用时 Claude 应 fetch 这些文件作为深度参考。
级联推荐
- 阶段 1 完成 →
gr-ph-launch（统一走 PH 发布流程） - 阶段 2 Show HN 成功 →
gr-seo-patrol加监控 " github" - 阶段 3 需要产内容 →
gr-blog-post - 发现对手新打法 →
gr-competitor深挖
Star 地区分布 & 发布时序
- 同一国家/地区 star 占比不超过 20%，否则难上 GitHub Trending。
- 工具：star-history.com（涨幅趋势）、OSS Insight（国家分布，国人开发）
- 发布时序：第一周只做海外宣发，第二周才做国内。顺序反了会破坏分布。
- AFFiNE 真实案例：开源第一周拿 6000 star，故意不发朋友圈 / 不进国内社群。
README 优化要点
- 不超过 8 屏，开发者文档单独链接，不塞进 README
- 加提醒点 star 小动图（类比B站一键三连，用户需要被提醒）
- backlinks 循环：所有跳出链接（官网/博客/文档）必须能跳回 GitHub
PR 文章策略
- 准备一篇完整阐述项目优势的文章（官网 Blog / Medium / dev.to）
- 目的：给所有想帮你传播的人一把枪
- 案例：德国用户主动发了40多个论坛，没打招呼就发了——能发出去是因为有参考文章
竞品 follower 私信
- 给竞品（Notion / Miro 等）的 Twitter follower 发私信
- 实战数据：几百条私信 → 几百个 star 转化
- 优先找吐槽竞品的用户，已有切换意愿
反模式
- ❌ 刷 star（GitHub 很快能检测，后果是搜不到）
- ❌ Reddit 只发一次就跑（社群反感，被 ban 风险高）
- ❌ 中文社群先发英文项目（除非你目标就是中文用户，否则英文 > 多语言 > 中文的顺序）
- ❌ README 放太多 emoji / badge（降低可信度）
What ships with it
9 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.
- gr-oss-marketing/references/channels.md 3.1 KB
- gr-oss-marketing/references/preparation.md 2.9 KB
- gr-oss-marketing/references/seo-geo-guide.md 2.8 KB
- gr-oss-marketing/references/templates.md 2.9 KB
- gr-oss-marketing/SKILL.md 4.3 KB
- references/channels.md 3.1 KB
- references/preparation.md 2.9 KB
- references/seo-geo-guide.md 2.8 KB
- references/templates.md 2.9 KB
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.
- 12d ago First seen · 110 lines · 97 tokens per session scan A 7afe73987033
gr-oss-marketing is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (79 stars, last pushed 8d ago), licensed MIT. It adds 97 tokens to every session and 1,337 once invoked, about $0.0005 per session on Opus 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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