BC mobile-app-launch-coach
End-to-end coach for indie devs / small teams launching mobile apps on iOS App Store + Google Play (and emerging app stores). Covers idea + ASO niche validation, native vs cross-platform (Swift/Kotlin/Flutter/React Native/Expo), App Store + Play Console submission and review survival (rejection patterns, IAP rules, privacy nutrition labels, AI-content disclosure 2026), monetization (subscription / one-time / freemium / ads / hybrid), App Tracking Transparency reality, ASO + paid UA + influencer + referral growth, retention and lifecycle messaging, exit options (acquisition, sale via Acquire.com / FE / direct). Use when builder asks about "should I build native or cross-platform", "App Store rejection", "Play Store policy", "ATT / IDFA", "subscription pricing tiers", "ASO keywords", "App Clip", "Instant App", "Apple Search Ads vs Meta UA", or transitioning a web SaaS to mobile. Triggers on phrases like "launch iOS app", "publish to App Store", "Google Play submission", "Flutter vs React Native", "Expo", "Apple subscription", "in-app purchase", "RevenueCat", "App Store rejection 4.3", "Privacy Manifest", "ASO ranking", "Apple Search Ads".
As a process C 54/100 · Has gaps — weak spots: result and completion, inputs and preconditions, running it twice
How to improve
- Shorten the description to 1024 characters.
- The SKILL.md body is over 5,000 tokens: move reference detail into references/ and load it when needed.
- 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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- error
description-longdescription is 1154 chars, limit 1024 - warning
body-longSKILL.md body ≈ 7088 tokens (recommended < 5000); move details to references/
Process rating: all ten parameters 54/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 10 mutating operations with no state check
- 60Tools and files. Uses tools (bash, python, node) that frontmatter does not declare
- 60Failures and branches. 2 branches
- 70When it triggers. States when to use, but not when not to
- 70Execution cost. Instruction body is 7088 tokens
- 100Steps. 221 steps
- 100Consistency. Name and required fields are in place
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low 11 top-level sections: this looks like several domains in one skill
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 1154: 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 20 example trigger phrases
- +4Structure: 12 headings
- +3Step-by-step instructions: 221 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 47.