AB asc-aso-audit
Run an offline ASO audit on canonical App Store metadata under `./metadata` and surface keyword gaps using Astro MCP. Use after pulling metadata with `asc metadata pull`.
The skill audits App Store Connect metadata locally and flags keyword gaps for ASO optimization. Works offline on your `./metadata` folder after running `asc metadata pull`. The code spans 2812 tokens with no lint errors and no critical findings. Quality score 91, process score 68—the gap suggests some logic isn't fully automated.
In practice: compatible with all major platforms from Claude to Cursor. No model runs or sandbox tests on record. If your metadata is in the right format and you need quick keyword analysis without leaving your machine, install it. For production ASO audits, expect to iterate.
Run an offline ASO audit on canonical App Store metadata under ./metadata and surface keyword gaps using Astro MCP. Use after pulling metadata with asc…
As a process B 68/100 · Nearly there — weak spots: when it triggers, progress reporting
How to improve
- 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
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 68/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (web) that frontmatter does not declare
- 60Result and completion. Output format stated, no completion criterion
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 56 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2812 tokens
- 100Running it twice. Mutating operations check current state
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)
- +1No license
- +2Single-language instructions
- +3Description length 170: enough signal without eating the budget
- +4Structure: 19 headings
- +3Step-by-step instructions: 56 items
- +3Output format is stated explicitly
- +4Has examples (9 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 91.