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Confirm the draft match request

confirm_match_request

Confirm one draft match request and add it to the matching pool. The other requests of the user do not change. It stays active until the user withdraws it. Call this ONLY after the user approves the exact stored text. Always pass its request_id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
request_idYesThe request_id from create_match_request or check_matches. Always name the exact request that the user approved, or asked you to withdraw.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations only say readOnlyHint=false and destructiveHint=false, so they don't reveal much. The description adds meaningful behavior: only the confirmed request changes, it becomes active until withdrawn, and confirmation requires the exact stored text. This goes beyond the structured annotations and helps an agent predict side effects.

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 compact and front-loaded: effect, non-effect, lifecycle, and precondition each get one short sentence. The instruction 'Always pass its request_id' is slightly redundant given the required schema, but it does not bloat the description significantly.

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 single-parameter tool with no output schema and no nested objects, the description covers everything an agent needs: what the tool does, what it does not do, how long the effect lasts, and the exact condition under which it should be called. Nothing important is missing.

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?

There is only one parameter and the schema description already explains that request_id comes from create_match_request or check_matches and should be the exact approved request. The description mostly repeats 'Always pass its request_id,' adding little beyond the schema. The schema coverage is 100%, so a baseline of 3 is appropriate.

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?

The description clearly states what the tool does: 'Confirm one draft match request and add it to the matching pool.' This distinguishes it from siblings like create_match_request and withdraw_match_request, and also clarifies scope by noting that other requests of the user do not change.

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 gives an explicit precondition: 'Call this ONLY after the user approves the exact stored text.' It also clarifies lifecycle behavior ('It stays active until the user withdraws it') and scope ('The other requests of the user do not change'). It doesn't name specific sibling alternatives, but the trigger condition is clear enough to route an agent correctly.

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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