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AC mercury

Mercury bank API for Digital 4 Jesus LLC (US entity). Use when the user asks about Mercury account balances, transactions, invoices, customers, or sending money. Triggers on phrases like "Mercury balance", "create invoice", "check Mercury", "list invoices", "create customer", "who owes me", "send money via Mercury", "Mercury statement", or any D4J LLC banking or AR question. Requires Mercury Plus for invoicing/customer endpoints. Credentials at ~/.secrets/mercury.env.

ClawHub Agent Skills author: Dewaldt Huysamen v1.0.0 MIT-0 4 files · 1 script body ≈ 423 tokens Open the sourceclawhub.ai↗ analyzed 4 d ago

As a process C 55/100 · Has gaps — weak spots: result and completion, inputs and preconditions, failures and branches

IntegrationFinancetype 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
92/100
safety, quality, tests
Safety 60%
89
Quality 40%
97
Run on models
none yet
Process rating
C
55/100
Has gaps
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
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 · 3

    ✓ No critical or high findings

    Medium and low: 3
    • medium Exfiltration net-credential-use scripts/mercury.sh:29
      Credential used in a network call (verify the destination is the intended service)
      curl -s --user "$TOKEN:" \
    • medium Exfiltration net-credential-use scripts/mercury.sh:35
      Credential used in a network call (verify the destination is the intended service)
      curl -s --user "$TOKEN:" -X "$method" "${BASE}${path}"
    • low Exfiltration net-credential-use references/api.md:7
      Credential used in a network call (verify the destination is the intended service) (the skill's own vendor host)
      curl --user "$MERCURY_API_TOKEN:" "https://api.mercury.com/api/v1/..."
      vendor-host

    Files scanned: 4. 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 55/100

    • 0Result and completion. Does not say what the result is
    • 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
    • 40Consistency. Frontmatter name (mercury) differs from the folder (mercury-bank)
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 7 steps
    • 100Execution cost. Instruction body is 423 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

    • +4Description does not say when NOT to use the skill (false activations)
    • +3Output format is not stated: the model decides each time
    • +2Single-language instructions
    • +5Description quotes 8 example trigger phrases
    • +3Description length 472: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 7 items
    • +4Has examples (2 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)
    • +3All 1 scripts are documented
    • +1License stated

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 97.

    External checks

    ClawHub: suspicious
    This Mercury banking helper is coherent, but it needs Review because it uses a live bank API token and can change financial records without enough safeguards.
    LLM: suspicious (high) · VirusTotal: · 29 May 2026