BF AI Product Global Launch Playbook
Every AI product launches into the same wall of noise — a thousand "we built an AI that…" posts a day. The breakout launches (Manus, Devin, AFFiNE) didn't get lucky; they managed the hype cycle deliberately. This playbook is the AI-specific GTM: waitlist mechanics, timing, and multi-market rollout for maximum day-one signal. What's inside: • AI product positioning — how to stand out when everyone claims the same capability • Global launch timing and market selection for day-one impact • Hype-cycle and waitlist tactics — building demand before you ship • KOL and influencer outreach for AI products • Community building in AI/ML spaces • Case studies — Manus, Devin, and AFFiNE breakout launches decoded 🇨🇳 AI 产品发布手册 — AI 特有 GTM、hype 周期管理、waitlist 打法、多市场 rollout、AI/ML KOL 触达。含 Manus/Devin/AFFiNE 拆解。 🇯🇵 AI製品ローンチ — AI特化GTM、ハイプサイクル管理、ウェイトリスト戦術、マルチマーケット展開。Manus/Devin/AFFiNE事例。 🇰🇷 AI 제품 런칭 — AI 특화 GTM, 하이프 사이클 관리, 웨이트리스트 전술, 멀티마켓 롤아웃. Manus/Devin/AFFiNE 사례. Triggers: "AI product launch" | "launch AI product" | "AI startup launch" | "AI GTM" | "waitlist strategy" | "hype cycle" | "AI product positioning" | "AI marketing" | "launch strategy" | "multi-market launch" | "AI 产品发布" | "AI 出海" | "waitlist 打法" | "AI製品ローンチ" | "AI 제품 런칭"
As a process F 31/100 · Will not run — References files that are not bundled: references/en/README.md, references/ja/README.md, references/ko/README.md
How to improve
- Shorten the description to 1024 characters.
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1245 chars, limit 1024 - warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
missing-refreference to a missing file: references/en/README.md - warning
missing-refreference to a missing file: references/ja/README.md - warning
missing-refreference to a missing file: references/ko/README.md - note
frontmatter-keyunknown frontmatter key "source"
Process rating: all ten parameters 31/100
- 0Tools and files. 3 referenced file(s) missing: references/en/README.md, references/ja/README.md, references/ko/README.md
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (AI Product Global Launch Playbook) differs from the folder (ai-launch-playbook)
- 100Steps. 19 steps
- 100Execution cost. Instruction body is 984 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 1244: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 15 example trigger phrases
- +4Structure: 9 headings
- +3Step-by-step instructions: 19 items
- +4Has examples (1 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 43.