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Payment processing fee scenario

privi_pro_stripe_fee_scenario
Read-only

Estimate merchant fees from explicitly supplied fixed and percentage assumptions. PAID ONLY: 5 prepaid credits; production billing required.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "amount_usd": "<amount_usd>",
      "rate_pct": "<rate_pct>",
      "fixed_fee_usd": "<fixed_fee_usd>"
    },
    "name": "privi_pro_stripe_fee_scenario"
  }
}

Input Schema

NameRequiredDescriptionDefault
rate_pctYes
amount_usdYes
fixed_fee_usdYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and closure are covered. The description adds genuinely new behavioral context the annotations lack: the tool is paid, consumes 5 prepaid credits per use, and requires production billing, which directly affects an agent's decision to invoke it. It does not describe the returned estimate, which is the remaining gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with no filler, and the core purpose is front-loaded ahead of the billing caveat. It is efficient, though the brevity comes partly at the cost of the missing unit and output detail noted elsewhere.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description should say what the estimate returns (total fee, effective rate, breakdown), and it does not. Combined with 0% parameter description coverage, an agent can call this tool but cannot confidently interpret or format the result. The billing disclosure is a positive, but the definition is under-complete for a three-required-number computation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% — all three parameters are bare numbers with no descriptions. The description only loosely maps to them by naming 'fixed and percentage assumptions', leaving critical ambiguities unresolved: whether rate_pct is 2.9 or 0.029, whether fees are in USD, and what amount_usd represents (transaction total vs. volume). For a zero-coverage schema the description should carry this burden and largely does not.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description pairs a specific verb ('Estimate') with a specific resource ('merchant fees') and scopes the inputs ('explicitly supplied fixed and percentage assumptions'), so an agent knows this is a pure calculation over caller-provided numbers rather than a data lookup. It does not differentiate against any named sibling, but the listed siblings are unrelated scenario tools, so the omission is low-cost.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'from explicitly supplied ... assumptions' implies this tool computes only from inputs the agent supplies and does no external fetching, which is a useful usage signal. However, there is no explicit when-to-use or when-not guidance, and no mention of what to do if assumptions are unknown, leaving usage context only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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