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Find someone to ask

find_someone_to_ask
Read-onlyIdempotent

Use this when someone wants a person to learn from or talk to but has not named one yet: "who should I learn negotiation from", "find me a stoic to talk to", "which historical figures are worth asking about leadership". Returns a grid of real people rendered in the conversation, each with a portrait and a role. The person picks one and the conversation continues in that voice.

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": "find_someone_to_ask"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoHow many to return, 1 to 24. Defaults to 12.
queryNoName or topic, for example "stoicism" or "Nietzsche".
categoryNoOptional category filter, for example "science" or "history-politics".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuine behavioral context beyond that: it returns a rendered grid of real people with portrait and role, and the selection hands off the conversation to that voice. It does not mention how many results to expect by default or what happens if no match is found.

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

Conciseness5/5

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

Front-loaded with the trigger condition, then the illustrative utterances, then the return behavior and follow-on flow in three tight sentences. Nothing is redundant with the title or schema.

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

Completeness4/5

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

No output schema exists, but the description describes the return (a rendered grid of people with portraits and roles) and the post-selection handoff, which is the important part for a discovery tool. Minor gap: no note on empty results or how limit interacts with the conversational follow-up.

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 limit, query and category are already documented with examples. The description adds no syntax or semantics beyond that, so the baseline of 3 applies. It does not explain that query accepts a name or a topic and how that interacts with category.

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

Purpose5/5

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

States a specific verb ('find') and resource ('someone to ask'), and immediately scopes it to the case where the user has not named a person. That scoping implicitly separates it from call_person/speak_as_person, which presumably require a named person, so an agent can route between them without opening schemas.

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?

Gives a clear triggering condition ('someone wants a person... but has not named one yet') plus three concrete example utterances that map to real user phrasings. It stops short of naming call_person or my_characters as the alternative for the already-named case, leaving that inference to the agent.

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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