SKILLEMALL.ai
GitHub ↗ RU Sign in

AB ai-traffic-tracking

When the user wants to track AI search traffic in GA4 or GSC. Also use when the user mentions "AI traffic," "ChatGPT referral," "Perplexity traffic," "AI Overviews," "GA4 AI sources," "AI search analytics," "track AI referrals," "AI search traffic," "Claude traffic," or "how to track AI traffic."

ClawHub Agent Skills author: Kostja Zhang v0.1.0 MIT-0 2 files body ≈ 852 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process B 66/100 · Nearly there — weak spots: inputs and preconditions, consistency, running it twice

ProcedureGoogle AnalyticsData and analyticsInfrastructureAI and agentstype and topics are labelled automatically from the skill text
Runs in: OpenClaw 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) Goose OpenCode
JSON
Technical rating
A
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
B
66/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

The same skill appears in 1 more place: ClawHub

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: 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 66/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 40Consistency. Frontmatter name (ai-traffic-tracking) differs from the folder (ai-traffic)
    • 55Failures and branches. 1 branches
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 35 steps
    • 100Execution cost. Instruction body is 852 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 10 example trigger phrases
    • +3Description length 297: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 35 items
    • +3Output format is stated explicitly
    • +4Has examples (1 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.

    External checks

    ClawHub: clean
    This is a markdown-only guide for tracking AI referral traffic in GA4/GSC and does not install code or access data on its own.
    LLM: benign (high) · VirusTotal: · 29 May 2026