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AC google-analytics-and-search-improve

Understand website goals and user journeys first, then analyze GSC/GA4 data and audit the live site to validate whether users behave as intended. Identify gaps between goals and reality, and produce actionable, goal-aligned improvement plans. Use when user wants to diagnose website problems, improve search rankings, optimize traffic, analyze Google Analytics or Search Console data, audit website performance, or create a data-backed improvement roadmap.

ClawHub Agent Skills author: Morvan v1.0.5 MIT-0 18 files body ≈ 4 799 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 64/100 · Has gaps — weak spots: inputs and preconditions

AnalyzerGoogle AnalyticsData and analyticsInfrastructuretype 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
96/100
safety, quality, tests
Safety 60%
98
Quality 40%
94
Run on models
none yet
Process rating
C
64/100
Has gaps
Inputs and preconditions w 11
0
When it triggers w 12
50
Failures and branches w 10
55
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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Exfiltration net-credential-use references/data-collection-reference.md:199
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -s "${PSI_BASE}&strategy=mobile${PSI_KEY_PARAM}" > "$DATA_DIR/data/psi_mobile.json"
      security skill
    • low Exfiltration net-credential-use references/data-collection-reference.md:200
      Credential used in a network call (verify the destination is the intended service) (documentation of a security skill)
      curl -s "${PSI_BASE}&strategy=desktop${PSI_KEY_PARAM}" > "$DATA_DIR/data/psi_desktop.json"
      security skill

    Files scanned: 18. 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 64/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 50When it triggers. No condition that starts the skill
    • 55Failures and branches. 1 branches
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70Execution cost. Instruction body is 4799 tokens
    • 100Steps. 39 steps
    • 100Consistency. Name and required fields are in place
    • 100Running it twice. Mutating operations check current state
    • 100Progress reporting. Reports progress
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing

    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 456: enough signal without eating the budget
    • +4Structure: 18 headings
    • +3Step-by-step instructions: 39 items
    • +3Output format is stated explicitly
    • +4Has examples (6 code blocks)
    • +4Reference files are cited in the instructions (7 of 7)
    • +3All 8 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 94.

    External checks

    ClawHub: clean
    This is a coherent website analytics and SEO audit skill, but it handles sensitive analytics data and credentials that users should protect carefully.
    LLM: benign (high) · VirusTotal: · 29 May 2026