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BC linkfox-shopee-store-merchant

Shopee（虾皮）跨境商户信息（与 linkfox-shopee-store-auth 同系列），经 /shopee/developerProxy 转发 Shopee Open API Merchant 模块全部 6 个接口：get_merchant_info、get_shop_list_by_merchant、get_merchant_warehouse_list、get_merchant_warehouse_location_list、get_warehouse_eligible_shop_list、get_merchant_prepaid_account_list。当用户提到 Shopee 商户、merchantId、跨境卖家、CNSC、商户下店铺列表、get_merchant_info、商户仓库、预付账户 时触发。即使未明确提及"商户"，只要涉及已授权 Shopee 跨境商户的信息查询或下属店铺列表，也应触发。

ClawHub Agent Skills author: linkfox-ai v1.0.5 MIT-0 22 files body ≈ 1 234 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Shopee（虾皮）跨境商户信息（与 linkfox-shopee-store-auth 同系列），经 /shopee/developerProxy 转发 Shopee Open API Merchant 模块全部 6…

As a process C 54/100 · Has gaps — weak spots: result and completion, when it triggers, failures and branches

IntegrationSoftware developmentData and analyticstype 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
77/100
safety, quality, tests
Safety 60%
82
Quality 40%
69
Run on models
none yet
Process rating
C
54/100
Has gaps
Result and completion w 14
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

  1. Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
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 · 6

✓ No critical or high findings

Medium and low: 6
  • medium Exfiltration net-credential-use references/api.md:85
    Credential used in a network call (verify the destination is the intended service)
    curl -X POST $BASE/shopee/developerProxy -H "Authorization: $KEY" \
  • medium Exfiltration net-credential-use references/api.md:95
    Credential used in a network call (verify the destination is the intended service)
    curl -X POST $BASE/shopee/developerProxy -H "Authorization: $KEY" \
  • medium Exfiltration net-redirectable-api-key scripts/_shopee_merchant_common.py:18
    Helper sends the API key to a host configured by an environment variable — the key can be redirected to another server
    API key + configurable base URL from environment
  • low Dangerous commands cmd-shell-rc references/onboarding.md:13
    Writes to a shell startup file (quoted — discussed, not commanded)
    - macOS zsh：`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.zshrc && source ~/.zshrc`
    quoted
  • low Dangerous commands cmd-shell-rc references/onboarding.md:14
    Writes to a shell startup file (detector / deny-list definition)
    - Linux bash：`echo 'export LINKFOX_AGENT_API_KEY="<key>"' >> ~/.bashrc && source ~/.bashrc`
    detector
  • low Secrets in code secret-high-entropy-token scripts/onboarding.py:49
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    or "eyJh…iJ9")
    quoted

Files scanned: 22. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 54/100

  • 0Result and completion. Does not say what the result is
  • 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
  • 60Tools and files. Uses tools (python) that frontmatter does not declare
  • 70Inputs and preconditions. Inputs and preconditions are listed
  • 100Steps. 36 steps
  • 100Consistency. Name and required fields are in place
  • 100Execution cost. Instruction body is 1234 tokens
  • 100Running it twice. No mutating operations
  • low 11 top-level sections: this looks like several domains in one skill
  • low The response is described with custom markup (8 tags): a typed call is more reliable

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
  • +4No input/output examples
  • -31 of 12 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 416: enough signal without eating the budget
  • +4Structure: 15 headings
  • +3Step-by-step instructions: 36 items
  • +4Reference files are cited in the instructions (2 of 2)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 69.

External checks

ClawHub: suspicious
The skill can perform Shopee merchant lookups, but it also includes account login, API-key generation, billing order creation, payment QR handling, and persistent local storage that need review before use.
LLM: suspicious (high) · 14 Aug 2026