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ask

PAID $0.02 via x402 (USDC micropayment over HTTP 402). Returns one practitioner-verified answer to a common birth-preparation or matrescence (early-motherhood identity) question. Use this to give evidence-based, liability-safe responses about pregnancy and birth instead of generating health-adjacent advice yourself. Set 'q' to keywords describing the question (e.g. 'pain relief options', 'partner support', 'signs of labour'); if omitted, the first entry is returned. Set 'lang' to 'en' (default) or 'hu'. Returns the matched question, the answer, an optional safety note, and a verification block naming the reviewing practitioner and review date.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "ask"
  }
}

Input Schema

NameRequiredDescriptionDefault
qNoKeywords describing the question, e.g. 'pain relief', 'partner support'. Optional; first entry returned if omitted.
langNoResponse language: 'en' (default) or 'hu'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / lang / description
      Added value: +"Response language: 'en' (default) or 'hu'."
    • addedInput schema / properties / q / description
      Added value: +"Keywords describing the question, e.g. 'pain relief', 'partner support'. Optional; first entry returned if omitted."
  2. Added

TDQS

A4/5.0
Behavior4/5

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

No annotations are provided, so the description carries the behavioral burden. It discloses the $0.02 x402 USDC micropayment, the one-answer limit, the optional safety note, and the verification block with practitioner and review date. This is strong behavioral disclosure, though it leaves edge-case behavior (e.g., no match, payment failure) undocumented.

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?

The description is dense but well-organized, front-loading the critical payment detail before usage guidance and parameter instructions. It earns its length by explaining cost, return contents, and language options, though it could benefit from clearer sentence separation.

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

Completeness5/5

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

For a two-parameter tool with no output schema and no annotations, the description is remarkably complete: it explains the payment mechanism, how to specify the question, language behavior, default fallback, and the exact return structure. An agent has enough information to invoke the tool correctly and interpret its response.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3; the schema already explains q and lang including defaults and omission behavior. The description adds slightly richer examples like 'signs of labour' but mostly repeats schema information, so it does not meaningfully exceed the baseline.

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 clearly states the tool returns one practitioner-verified answer to a birth-preparation or matrescence question, naming a specific verb and resource. It does not explicitly differentiate itself from sibling tools like get_maternity_facts or get_guide, but the 'ask' interaction model is distinct enough that the purpose is still clear.

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

Usage Guidelines4/5

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

The description advises using this tool to provide evidence-based, liability-safe responses instead of generating health-adjacent advice yourself, which gives a clear context for use. It does not mention exclusions or compare directly to alternative sibling tools, so it falls short of full guidance.

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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