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 agentmods add skills/gingiris-1031/gingiris-skills/startup-launchnpx skills add Gingiris-1031/gingiris-skills --skill startup-launchgit 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/startup-launch)<a href="https://agentmods.dev/skills/gingiris-1031/gingiris-skills/startup-launch"><img src="https://agentmods.dev/badge/skills/gingiris-1031/gingiris-skills/startup-launch.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00044 | $0.01069 |
| Opus 5 | $0.00022 | $0.00535 |
| Sonnet 5 | $0.00009 | $0.00214 |
| Haiku 4.5 | $0.00004 | $0.00107 |
Grade A, and why
startup-launch 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 5d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
⚠️ 区分 B2B 与 2C
本 skill 默认偏 dev / 开源 / B2B SaaS。若产品是 2C 消费品 / 教育 / 应用 / 游戏：核心指标换成 D1/D7/D30 留存、激活率、病毒系数 K（非 MRR/CAC/LTV）；冷启动渠道换成垂类社区 / 短视频 / 垂直 KOL（非 PH/HN/LinkedIn）。完整 2C 适配指南 + 各国渠道公开数据见 → gingiris-seo-geo/references/2c-adaptation.md。
Startup Launch Day Playbook — Hour-by-Hour Checklist
📦 Install
clawhub install startup-launch
What you get after installing:
- Hour-by-hour execution plan from T-12h to 72h post-launch
- Coordinated multi-channel activation sequence
- Crisis management playbook (site down, negative feedback, competitor attacks)
Your launch day is ONE shot. This playbook gives you an hour-by-hour execution plan so nothing falls through the cracks. From T-minus-12-hours prep to the 72-hour post-launch sprint.
What You'll Learn
- T-12h: Final checks (servers, links, payment, copy)
- Hour 0: Coordinated channel activation sequence
- Hours 1-6: Real-time monitoring and engagement tactics
- Hours 6-24: Second-wave amplification
- 72-hour post-launch momentum playbook
- Crisis management (site down, negative feedback, competitor attacks)
Who This Is For
- Founders with a launch date already set
- Teams who have the product ready but need execution confidence
- Anyone who's been burned by a disorganized launch before
Traffic Engineering for Launch Day (2026 field addendum)
Plan the day as arithmetic, not vibes
Fix a total-visits target, then reverse-engineer per-channel quotas — each with its own UTM short link and a named owner. Anonymized reference (an AI Agent product, late 2025): a 500K-visit launch day was assembled as ~400K from 40 creator quote-tweets, plus ~20K each from Reddit threads, geo-targeted YouTube ads, and messaging-group distribution. Final tally: ~800 signups at $6.25 per registration. The lesson cuts both ways — traffic is buildable to spec; conversion is the bottleneck you can't buy.
What ships with it
5 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.
- 5d ago First seen · 84 lines · 44 tokens per session scan A 17d589cb6757
startup-launch is a skill published in the GitHub repository Gingiris-1031/gingiris-skills (77 stars, last pushed today), licensed MIT. It adds 44 tokens to every session and 1,069 once invoked, about $0.0002 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.
Other skills, from other repositories
gingiris-launch
🇺🇸 Product Hunt Launch Playbook 2026 — AI product go-to-market SOP from 30x #1 Product Hunt winners (Manus, Devin, AFFiNE). KOL outreach templates, UGC growth tactics, Reddit marketing, global launch checklist, hunter network, email sequences, viral momentum, timing & timezone strategy. 🇨🇳 AI产品全球发布行动指南 — 基于…
design-go-to-market-strategy
Use when launching a new product, entering a new market, or planning the commercialization approach for a startup or new business unit.
gtm-metrics
Build a GTM metrics system for SaaS: funnel conversion, pipeline velocity, win rates, CAC, payback, NRR, sales efficiency, growth accounting, and executive dashboards. Use when creating metrics dashboards, board reports, revenue reviews, operating cadence, or diagnosing growth constraints.
a-b-testing
Design statistically sound GTM experiments for copy, channels, landing pages, sequencing, pricing, and funnel conversion. Produces hypothesis, sample-size logic, success metrics, test plan, analysis method, and scale/stop/kill recommendation. Use when planning A/B tests, split tests, or experiment roadmaps.
attribution
Build practical B2B attribution models across first touch, lead creation, opportunity creation, multi-touch, account-based influence, and sales-sourced revenue. Produces model comparison, UTM governance, source-of-truth rules, and channel ROI view. Use when marketing and sales disagree on source or ROI.
campaign-analytics
Analyze campaign performance from deliverability through revenue: delivery, engagement, replies, meetings, SQOs, pipeline, CAC, and payback. Produces diagnostic scorecard, root-cause analysis, benchmark comparison, and next-action plan. Use when deciding whether to scale, fix, or kill campaigns.