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BlindWrite MCP

BlindWrite MCP

by ygstudio-game
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

benchmark_submit_vote

Vote in a blind A/B writing evaluation by selecting A, B, or tie, with optional reasoning and dimension ratings to support unbiased preference analytics.

Instructions

Submit a blind user preference vote ('A', 'B', or 'tie') with optional reasoning and dimension ratings.

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": {
      "battle_id": "<battle_id>",
      "choice": "<choice>"
    },
    "name": "benchmark_submit_vote"
  }
}

Input Schema

NameRequiredDescriptionDefault
choiceYesThe winner ('A', 'B', or 'tie')
reasonNoOptional user reasoning explaining the vote
battle_idYesThe battle ID being voted on
dimension_scoresNoOptional dimension ratings e.g. {"clarity": 5, "tone": 4, "conciseness": 5}

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.8/5.0
Behavior3/5

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

The description discloses the blind nature of the vote and optional fields, but it does not mention any side effects such as whether votes are updatable, idempotent, or require authentication. Since no annotations are provided, this is acceptable but not thorough.

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?

The description is concise, with two sentences that cover the essential action and optional parameters without unnecessary detail or redundancy.

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?

The description provides sufficient context for the tool's purpose and parameters, but it does not specify the response format or any post-submission behavior. Given the lack of an output schema, this is a minor gap.

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?

The schema already fully describes all parameters, and the description repeats the same information without adding new semantic nuances (e.g., the meaning of 'dimension_scores' or constraints beyond the schema). It meets the baseline for high schema coverage.

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 the tool's function: submitting a blind preference vote with a specific set of choices (A, B, or tie) and optional reasoning/ratings. It is distinct from sibling tools that compare, analyze, or generate results.

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 description implies usage by its action-oriented wording, but it does not explicitly state when to prefer this tool over alternatives or provide context about prerequisites (e.g., needing a valid battle_id from a duel).

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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