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-go-globalgit 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-go-global)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/gingiris-go-global"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/gingiris-go-global.svg" alt="Measured on agentmods" 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 | $0.00534 | $0.05604 |
| Opus 5 | $0.00267 | $0.02802 |
| Sonnet 5 | $0.00107 | $0.01121 |
| Haiku 4.5 | $0.00053 | $0.00560 |
Grade A, and why
gingiris-go-global 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 7d 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 — 313 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚠️ 使用前：确认你的产品类型
本 SOP 默认场景：开发者工具 / 开源 / B2B SaaS 出海（Phase 渠道默认 Product Hunt / HN / Reddit / GitHub）。
如果你的产品是 2C 消费品 / 教育 / 应用 / 游戏，以下必须替换：
| 环节 | 默认（B2B/开源） | 2C 建议 |
|---|---|---|
| 前 100 用户渠道 | PH / HN / GitHub / LinkedIn | 垂类社区(Reddit/小红书/知乎/Naver 카페) + 短视频(TikTok/抖音/YouTube) + 垂直 KOL |
| Launch 打法 | Product Hunt 打榜 | 2C 下 PH 受众错配、ROI 低；改"红利内容 + 免费钩子 + 社区分发" |
| 核心指标 | MRR / CAC / LTV | D1/D7/D30 留存、激活率、病毒系数 K |
| 增长引擎 | Freemium 试用 → 销售 | 免费产品当钩子(PLG)，先拿 100 真实用户再放量 |
| 选渠道方法 | 按"科技人聚集地" | 按地区公开数据选第一平台(如印尼/泰国短视频已反超 Facebook) |
完整 2C 渠道数据库（各国 MAU + 公开来源）见 → gingiris-seo-geo/references/2c-adaptation.md
AI 产品/SaaS 企业出海完整 SOP
作者：Iris (生姜iris) | 版本：1.0.0
核心理念
出海不是"发英文内容 + 上 Product Hunt"。真正的主线是：
- 找到最窄、最愿意付费的用户
- 用竞品和用户语言定义一句话定位
- 把官网、README、Demo、社区、转化路径做成闭环
- 在 24-48 小时内集中打出可信流量峰值
- 峰值之后立刻转向用户访谈、转化率和商业化
- 用内容、社区、SEO、生态合作把一次发布沉淀成长期资产
一句话：先把桶补好，再开水龙头。
全流程框架
Phase 0：出海前判断
回答四个问题：
- 你靠谁赚钱？
- 这批人现在用什么替代方案？
- 他们在哪些渠道主动讨论这个问题？
- 他们为什么现在就愿意切换或付费？
回答不出来 → 不要做 launch，先做用户访谈和竞品拆解。
Phase 1：竞品调研
- 只选最多 3 个对标（用户画像一致、商业模式一致、已跑通商业化）
- 用 web.archive.org 拆竞品官网历史（每阶段一句话介绍、CTA 变化、客户 logo 出现时间）
- 拆渠道：Twitter/X、YouTube、Reddit、SEO（竞品词/alternative/场景词/问题词）
- 落到一张表：哪个渠道适合你、为什么、第一波怎么打
Phase 2：定位与官网
- 一句话公式：
[差异点] + [对标产品] + for [目标用户/场景] - 官网首屏 10 秒内说清：这是什么、给谁用、替代什么、为什么更好、下一步点哪里
- 结构：价值主张+CTA → Use Case → Trusted By → 功能/对比/定价/FAQ
Phase 3：前 100 个用户
PMF 前不要花超过 $1000 找前 100 个用户：
- 挖竞品活跃用户（近 3 月评论过竞品、表达不满）
- LinkedIn 精准建联（按职能/行业/公司规模/国家/工具）
- Reddit / Twitter 关键词监听（竞品名、alternative to、looking for）
- Fiverr / 服务市场验证付费需求
Phase 4：用户访谈
- 必须共享屏幕、看竞品使用、用户说 80% 你说 20%
- 优先访谈：Top 10 付费用户 / Token 消耗 Top 10 / 连续使用 3-7 天的 Beta 用户
- 理解上下游 workflow：前一步、后一步、替代方案、卡点、哪一步愿意付钱
Phase 5：Beta 用户转增长资产
- 创始人亲自 Welcome Letter + 专属社区
- 连续使用 3-7 天后推动社媒分享
- 把用户总结出的产品差异改写成官网和社媒文案
渠道 SOP 摘要
| 渠道 | 核心要点 |
|---|---|
| 开源 Launch | 48h 集中引爆，所有入口回 GitHub README |
| Product Hunt | Badge 战，非流量战；organic community engagement |
| 潜水 1-2 周，80% 干货 + 20% 产品；不要跨社区复制 | |
| SEO/GEO | 先做 alternative / use case / 模板页 / 对比页 |
What ships with it
6 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.
- 7d ago First seen · 313 lines · 534 tokens per session scan A 2fc02b88a2cc
gingiris-go-global is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (79 stars, last pushed 3d ago), licensed MIT. It adds 534 tokens to every session and 5,604 once invoked, about $0.0027 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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