BD asc-apple-ads
Use when managing Apple Ads with asc, including OAuth profiles, ad-account discovery, Platform API v1 campaigns and targeting, reports, assets, recommendations, guarded mutations, raw requests, and Campaign Management API v5 migration.
The skill promises full Apple Ads control via App Store Connect: OAuth, account discovery, Platform API v1 campaigns, reports, assets, recommendations, and Campaign Management API v5 migration. One instruction file with 3236 tokens, no scripts, no critical errors.
Grade B with 84% quality indicates working state, but process score of 43 flags structural gaps. Safety at 100, no medium-level findings. Support for eight platforms from Claude to OpenClaw means compatibility, yet no model runs show how it handles real Apple API calls in practice.
Install if you already manage App Store Connect and accept that the instruction will need tweaking for your specific workflows.
Use when managing Apple Ads with asc, including OAuth profiles, ad-account discovery, Platform API v1 campaigns and targeting, reports, assets…
As a process D 43/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- note
edit-residuethe text marks something as outdated (lines 9, 17, 54, 226, 242): check that old rules are not kept next to new ones — the full check reads the text for contradictions
Process rating: all ten parameters 43/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 14 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 100Steps. 13 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3236 tokens
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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 235: enough signal without eating the budget
- +4Structure: 9 headings
- +3Step-by-step instructions: 13 items
- +4Has examples (19 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.