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App Store Optimization toolkit for researching keywords, optimizing metadata, and tracking mobile app performance on Apple App Store and Google Play Store.
Passed 15 of 22 test cases with the skill, and 10 of 22 without it.
and 2 more in the full report
5 fixed10 passed either way7 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
We have a list of raw seed terms for a travel planning app: 'trip planner, flight tracker, itinerary maker'. We want to analyze keyword difficulty, search relevance, and priority scores locally using command-line scripts. What command executes this analysis?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies executing `python scripts/keyword_analyzer.py --keywords "trip planner, flight tracker, itinerary maker"` | Missed | Passed |
The instructions your model reads when the skill loads.
ASO tools for researching keywords, optimizing metadata, analyzing competitors, and improving app store visibility on Apple App Store and Google Play Store. This file is a lean map — execute a task by loading the matching reference below.
keyword_analyzer, metadata_optimizer, competitor_analyzer, aso_scorer, ab_test_planner, review_analyzer, launch_checklist, localization_helper (stdlib only, analyze data you provide)Before generating, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
python scripts/keyword_analyzer.py --keywords "todo,task,planner"
python scripts/metadata_optimizer.py --platform ios --title "App Title"
python scripts/aso_scorer.py --app-id com.example.app
test cases passed, vs 10 / 22 without
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