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BC ecommerce-website-data

Free, instant access to ecommerce data on 10M+ ecommerce stores and ecommerce websites. Search Shopify stores, WooCommerce sites, and more. Capabilities: (1) Search ecommerce stores by keyword & filters (2) Full store analytics with 100+ data fields (3) Historical GMV & traffic trends (4) Installed apps & tech stack (5) LinkedIn contacts. Use when the user wants ecommerce website data, Shopify store analytics, competitor analysis, revenue trends, or decision-maker contacts. Triggers: "search ecommerce stores selling pet food", "find Shopify stores in US", "ecommerce website data for ooni.com", "what apps does X use", "revenue trend for X", "competitor analysis".

ClawHub Agent Skills author: eccompass.ai v1.2.18 MIT-0 8 files body ≈ 2 645 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process C 58/100 · Has gaps — weak spots: inputs and preconditions, failures and branches, running it twice

AnalyzerShopifyWordPressData 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
B
87/100
safety, quality, tests
Safety 60%
80
Quality 40%
98
Run on models
none yet
Process rating
C
58/100
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

What is at stake

Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.

Exfiltration medium severity

Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.

If you install

The instructions or scripts send data out: environment variables, keys, file contents, chat history. You may never notice, because the agent performs the upload as "part of the task".

For the author

If the upload is not needed for the task, remove it: catalogs flag such skills and delist them. If it is needed, name the destination explicitly, say what leaves the machine, and give the user a switch.

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 · 4

    ✓ No critical or high findings

    Medium and low: 4
    • medium Exfiltration net-credential-use SKILL.md:257
      Credential used in a network call (verify the destination is the intended service)
      curl -H "APEX_TOKEN: $APEX_TOKEN" https://api.eccompass.ai/public/api/v1/domain/ooni.com
    • medium Exfiltration net-credential-use SKILL.md:265
      Credential used in a network call (verify the destination is the intended service)
      curl -H "APEX_TOKEN: $APEX_TOKEN" https://api.eccompass.ai/public/api/v1/historical/ooni.com
    • medium Exfiltration net-credential-use SKILL.md:273
      Credential used in a network call (verify the destination is the intended service)
      curl -H "APEX_TOKEN: $APEX_TOKEN" https://api.eccompass.ai/public/api/v1/installed-apps/ooni.com
    • medium Exfiltration net-credential-use SKILL.md:281
      Credential used in a network call (verify the destination is the intended service)
      curl -H "APEX_TOKEN: $APEX_TOKEN" https://api.eccompass.ai/public/api/v1/contacts/ooni.com

    Files scanned: 8. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    • note frontmatter-key unknown frontmatter key "website"
    • note frontmatter-key unknown frontmatter key "requires"

    Process rating: all ten parameters 58/100

    • 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
    • 30Running it twice. 2 mutating operations with no state check
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Steps. 11 steps
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2645 tokens
    • low 14 top-level sections: this looks like several domains in one skill

    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)
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +3Description length 670: enough signal without eating the budget
    • +4Structure: 23 headings
    • +3Step-by-step instructions: 11 items
    • +3Output format is stated explicitly
    • +4Has examples (11 code blocks)
    • +4Reference files are cited in the instructions (2 of 2)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 98.

    External checks

    ClawHub: suspicious
    The skill appears to perform the advertised ecommerce lookup work, but it asks users to handle an API token unsafely and exposes business contact data without clear privacy or acceptable-use guardrails.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026