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BC ads-snapchat

Audit Snapchat Ads measurement, Snap Pixel and Conversions API, mobile and app campaigns, creative, AR and catalog formats, audiences, budgets, brand safety, and reporting. Use for Snapchat Ads, Snap Ads, Snap Pixel, Snapchat Conversions API, AR Lens ads, app-install campaigns, or Snapchat dynamic product ads.

AgriciDaniel/claude-ads Agent Skills author: AgriciDaniel MIT 1 file body ≈ 375 tokens Open the sourcegithub.com↗ analyzed 4 d ago

Audit Snapchat Ads measurement, Snap Pixel and Conversions API, mobile and app campaigns, creative, AR and catalog formats, audiences, budgets, brand safety…

As a process C 62/100 · Has gaps — weak spots: when it triggers, inputs and preconditions, failures and branches

AnalyzerMarketingtype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
93/100
safety, quality, tests
Safety 60%
100
Quality 40%
83
Run on models
none yet
Process rating
C
62/100
Has gaps
Inputs and preconditions w 11
0
Failures and branches w 10
0
Progress reporting w 2
0
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 62/100

    • 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
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 12 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 375 tokens
    • 100Running it twice. No mutating operations

    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)
    • +4No input/output examples
    • +1No license
    • +2Single-language instructions
    • +3Description length 311: enough signal without eating the budget
    • +4Structure: 4 headings
    • +3Step-by-step instructions: 12 items
    • +3Output format is stated explicitly

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 83.