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 shawnpang/startup-founder-skills --skill launch-strategygit clone --depth 1 https://github.com/shawnpang/startup-founder-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/shawnpang/startup-founder-skills/launch-strategy)<a href="https://agentmods.dev/skills/shawnpang/startup-founder-skills/launch-strategy"><img src="https://agentmods.dev/badge/skills/shawnpang/startup-founder-skills/launch-strategy/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/shawnpang/startup-founder-skills/launch-strategy"><img src="https://agentmods.dev/badge/skills/shawnpang/startup-founder-skills/launch-strategy.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00041 | $0.02010 |
| Opus 5 | $0.00020 | $0.01005 |
| Sonnet 5 | $0.00008 | $0.00402 |
| Haiku 4.5 | $0.00004 | $0.00201 |
Grade A, and why
launch-strategy 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 11d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- launch-strategy — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Launch Strategy
When to Use
- Planning a launch for a new product, course, program, or major feature.
- Designing a pre-launch content sequence to build anticipation and desire.
- Structuring a launch funnel with cart open/close mechanics.
- Preparing a JV/affiliate launch with partner recruitment.
- Building an evergreen launch funnel for ongoing automated sales.
- Deciding between seed launch, internal launch, JV launch, or evergreen launch.
- Applying the Product Launch Formula or similar sequenced launch methodology.
Context Required
- From startup-context: product description, target audience, value proposition, existing audience size, email list size and engagement, brand voice.
- From the user: what is being launched and the core transformation it provides, launch type (seed, internal, JV, evergreen), launch timeline and cart open/close dates, pricing and offer stack (product + bonuses + guarantee), existing assets (testimonials, case studies, content), budget for ads or affiliate commissions, team capacity, and any previous launch experience.
Workflow
- Define the offer — Clarify exactly what is being sold, the transformation it provides, the price point, and the offer stack (main product + bonuses). Total perceived value should be 10x+ the price.
- Select the launch type — Based on audience size, product maturity, and goals:
- Seed Launch — Small list, new product. Validate and get testimonials before going big.
- Internal Launch — Launch to your own list with a full pre-launch content sequence.
- JV Launch — Partner with affiliates who promote to their lists for broader reach.
- Evergreen Launch — Automated version of a live launch, triggered by opt-in.
- Build the launch list — Create a dedicated opt-in to identify the most interested prospects. This is your hottest segment. Build this list before creating pre-launch content.
- Create pre-launch content (PLC) — Develop 3-4 pieces of high-value content using the Sideways Sales Letter structure (see framework below). Each piece delivers standalone value while advancing the sale.
- Write the launch email sequence — Plan emails for every phase: PLC releases, cart open announcement, mid-launch social proof, final push urgency, and cart close deadline.
- Build the sales page — Create the sales page with offer stack, testimonials, guarantee, and countdown timer. The page should make the buying decision feel obvious.
- Recruit JV partners (if applicable) — Reach out to potential affiliates 4-6 weeks before launch. Provide swipe files, tracking links, and leaderboard incentives.
- Execute the launch — Release PLCs on schedule, open cart, send emails, engage with prospects in real time. Most sales happen in the last 24 hours.
- Close the cart and debrief — When the cart closes, it closes. Follow up with non-buyers. Analyze results and plan improvements for the next launch.
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.
- 11d ago First seen · 109 lines · 41 tokens per session scan A 9c4b45aeb6d9
launch-strategy is a skill published in the GitHub repository shawnpang/startup-founder-skills (321 stars, last pushed 5mo ago), licensed MIT. It adds 41 tokens to every session and 2,010 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.
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