Content
75%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 strong, well-structured instruction-only skill: a clear four-phase workflow, concrete audit criteria with exact platform limits, defined weights, and a complete output template. The main gaps are calibration (scoring bands exist only for Title, not the other nine factors) and the absence of any validation checkpoint before the final scorecard is produced.
Suggestions
Add scoring bands (like the Title section's 9-10/7-8/4-6/0-3 anchors) to each of the remaining nine factors so scores are calibrated consistently rather than left to judgment.
Add a validation step before output, e.g. re-check that every factor score is justified by at least one cited observation from the collected metadata, and confirm data completeness before scoring.
Consider moving iOS-only and Android-only factor criteria into a per-platform reference file so the main audit flow stays platform-neutral.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is a dense framework of concrete criteria (30-character limits, 100 keyword-field characters, 4.5+ stars, 15-30 second videos) with almost no explanation of concepts Claude already knows. It falls just short of the 'every token earns its place' anchor due to the boilerplate opener ('You are an expert in App Store Optimization...') and a few table rows that restate the obvious (e.g., 'Readability | Natural reading, not keyword-stuffed?'). | 4 / 5 |
Actionability | Concrete and executable for an instruction-only skill: exact weights, a 0-10 scoring scale, a full output template with ASCII bar placeholders, and a fallback ('If not available, ask the user to provide their current metadata'). The gap keeping it below fully-executable guidance is that scoring bands are defined only for Title (9-10/7-8/4-6/0-3) while the other nine factors have checklists but no calibration for assigning scores. | 4 / 5 |
Workflow Clarity | The sequence Initial Assessment -> Data Collection -> Audit Framework -> Output Format is clearly ordered, with explicit input gathering (App ID, country, platform) and a fallback loop when MCP data is unavailable. It misses anchor 5 because there is no validation checkpoint (e.g., confirming data completeness or cross-checking a low score against the underlying metadata) before producing the final scorecard. | 4 / 5 |
Progressive Disclosure | The skill is self-contained with no bundle files, and the body is well organized into clean per-factor sections with consistent tables and a defined output format. It sits at anchor 4 rather than 5 because the ~173-line, 10-factor framework (including iOS-only sections interleaved with universal ones) is borderline content that could be split into per-platform reference files, a minor organization gap. | 4 / 5 |
Total | 16 / 20 Passed |