Content
68%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A focused, actionable skill body with good structure, concrete code, and useful tables/templates. The main weakness is workflow_clarity: the recovery/prompt campaigns operate at scale on users but lack explicit validation checkpoints and feedback loops before prompting.
Suggestions
Add explicit validation gates to the prompt campaign (e.g. 'verify each user segment meets all session/crash criteria before prompting') and a validate→fix→retry loop for the recovery workflow.
Tighten the opening 'Why Ratings Matter' section, which lightly restates ASO concepts Claude already knows, to improve token efficiency.
Fill the Output Format placeholders with a short worked example so the template is immediately usable rather than schematic.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Mostly lean and well-organized with tables and code that earn their place, though a few explanatory lines (e.g. 'Ratings are an App Store ranking signal and a conversion factor') lightly restate concepts Claude already knows. | 4 / 5 |
Actionability | Provides concrete executable Swift and Kotlin snippets plus specific session/threshold criteria and an output template, with only minor gaps such as placeholder values that the user must fill in. | 4 / 5 |
Workflow Clarity | Recovery and prompt campaigns are sequenced with a day-by-day timeline, but the batch 'aggressive prompt campaign' lacks validation checkpoints to verify criteria are met before prompting, and there is no explicit validate/fix/retry loop. | 3 / 5 |
Progressive Disclosure | Well-structured with clear section headers and a concise overview, and it cleanly defers detail to related skills; no bundle files exist, so references are limited to sibling-skill pointers rather than separate detailed files. | 4 / 5 |
Total | 15 / 20 Passed |