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AF app-store-optimization

App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store. Use when the user asks about ASO, app store rankings, app metadata, app titles and descriptions, app store listings, app visibility, or mobile app marketing on iOS or Android. Supports keyword research and scoring, competitor keyword analysis, metadata optimization, A/B test planning, launch checklists, and tracking ranking changes.

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 18 files body ≈ 3 987 tokens Open the sourcegithub.com↗ analyzed 2 d ago

App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on…

As a process F 49/100 · Will not run — References files that are not bundled: ../content-creator/, ../marketing-demand-acquisition/, ../marketing-strategy-pmm/

AnalyzerWriting and documentsMedia and videotype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
90/100
safety, quality, tests
Safety 60%
100
Quality 40%
76
Run on models
none yet
Process rating
F
49/100
Will not run
References files that are not bundled: ../content-creator/, ../marketing-demand-acquisition/, ../marketing-strategy-pmm/
Tools and files w 18
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

How to improve

  1. The text references files that are not there: add them or drop the references.
For the model run — optional
  • 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: 18. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning missing-ref reference to a missing file: ../content-creator/
  • warning missing-ref reference to a missing file: ../marketing-demand-acquisition/
  • warning missing-ref reference to a missing file: ../marketing-strategy-pmm/
  • note frontmatter-key unknown frontmatter key "triggers"

Process rating: all ten parameters 49/100

Will not run. References files that are not bundled: ../content-creator/, ../marketing-demand-acquisition/, ../marketing-strategy-pmm/
  • 0Tools and files. 3 referenced file(s) missing: ../content-creator/, ../marketing-demand-acquisition/, ../marketing-strategy-pmm/
  • 0Inputs and preconditions. Does not say what the process needs to start
  • 0Failures and branches. Linear process with no failure handling
  • 30Running it twice. 10 mutating operations with no state check
  • 60Result and completion. Output format stated, no completion criterion
  • 70When it triggers. States when to use, but not when not to
  • 100Steps. 138 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 3987 tokens
  • 100Progress reporting. Reports progress
  • low 12 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

  • +5Description has no quoted example phrases that should trigger the skill
  • +4Description does not say when NOT to use the skill (false activations)
  • -5TODO / placeholder text left in the skill
  • +1No license
  • +2Single-language instructions
  • +3Description length 532: enough signal without eating the budget
  • +4Structure: 37 headings
  • +3Step-by-step instructions: 138 items
  • +3Output format is stated explicitly
  • +4Has examples (8 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)
  • +3All 8 scripts are documented

Quality base 70; lint remarks subtract, signals add up to 100. Result: 76.