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Read 引力AI candidate details

fitmeet_people_details

Read or compare up to five candidates from a still-valid query created by this connection. Use only presentation IDs returned by that query. Reading details does not authorize contact.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryIdYes
candidatePresentationIdsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
scopeYes
funnelYes
statusYes
purposeNo
queryIdYes
receiptYes
marketIdYes
revisionYes
expiresAtYes
candidatesYes
observedAtYes
environmentYes
marketLabelNo
marketScopeNo
reasonCodesYes
evidenceScopeYes
searchContextNo
searchProgressNo
contactAuthorizedYes
queryRequirementsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Adds genuinely useful behavior beyond the annotations: the query must still be valid, IDs must originate from that query, and reading details carries no contact authorization. It does not address why annotations mark this a read as non-read-only and non-idempotent, which is a notable omission for an agent judging side effects or retry safety.

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?

Three short sentences, front-loaded with the action and scope, then the input constraint, then the authorization boundary. No filler and nothing repeated from schema or annotations.

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?

An output schema exists, so return values need no explanation, and the description covers preconditions, input provenance, and the contact boundary. It leaves unclear what 'compare' produces behaviorally and why the operation is annotated non-idempotent, which is the only real gap for a two-parameter tool.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry the load, and it does: it ties queryId to a live query created by this connection and candidatePresentationIds to IDs returned by that query, and its 'up to five' matches the maxItems constraint. It omits the required ID prefixes (pquery_/pcpres_) encoded in the patterns, keeping it below 5.

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?

States a specific verb (read/compare) on a specific resource (candidates from a query created by this connection), with a hard scope of up to five. This implicitly separates it from fitmeet_people_search, which originates queries rather than consuming them, but it never names a sibling explicitly, so 4 rather than 5.

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 precondition (query must still be valid) and a hard input constraint (use only presentation IDs returned by that query), plus a scope limit of five. No alternatives are named for the case where the query has expired or the caller has no IDs, so it stops short of a 5.

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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