BC gingiris-aso-growth
🇺🇸 ASO & Mobile App Growth Playbook 2026 — Complete App Store Optimization guide. ASO keyword ranking, App Store & Google Play listing optimization, app cold start, UGC creator operations, TikTok/Instagram/YouTube Shorts marketing, AI-matrix content scaling, mobile user acquisition. 🇨🇳 ASO 增长与 App 冷启动权威指南 — 从应用商店优化到 UGC 运营、多平台内容策略、AI 辅助内容创作的完整实操手册。 🇯🇵 ASO&アプリコールドスタート成長ガイド — App Store最適化からUGC運営、マルチプラットフォーム戦略、AIマトリックスまで。 🇰🇷 ASO 및 앱 콜드 스타트 성장 플레이북 — 앱스토어 최적화부터 UGC 운영, 멀티플랫폼 전략, AI 매트릭스까지. Triggers: "ASO" | "App Store Optimization" | "ASO keywords" | "App Store ranking" | "Google Play optimization" | "app cold start" | "app launch" | "mobile app growth" | "user acquisition" | "UA" | "UGC creator" | "TikTok marketing" | "Instagram Reels" | "YouTube Shorts" | "creator matrix" | "app growth" | "应用商店优化" | "App冷启动" | "UGC运营" | "矩阵号"
As a process C 53/100 · Has gaps — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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: 8. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when") - note
frontmatter-keyunknown frontmatter key "source"
Process rating: all ten parameters 53/100
- 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
- 100Tools and files. No external tools needed
- 100Steps. 35 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 1221 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 847: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +5Description quotes 16 example trigger phrases
- +4Structure: 18 headings
- +3Step-by-step instructions: 35 items
- +4Reference files are cited in the instructions (5 of 5)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 73.