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ygstudio-game

BlindWrite MCP

benchmark_compare_models

Compare two AI models head-to-head using accumulated pairwise benchmark battle history to reveal which performs better.

Instructions

Compare two AI models head-to-head using accumulated pairwise benchmark battle history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNoOptional category filter for head-to-head records
model_a_idYesFirst model ID to compare
model_b_idYesSecond model ID to compare

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

B3.4/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It does suggest a read-only, historical operation via 'accumulated pairwise benchmark battle history', but it does not disclose return format, edge cases, rate limits, permissions, or whether any state is changed.

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 a single focused sentence with no filler. Every word contributes meaning, and the core action and data source are front-loaded.

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

Completeness2/5

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

With no output schema and no annotations, the description leaves important context unstated: what the returned comparison looks like, how category filtering behaves, and what happens when no battle history exists. It is enough for basic invocation but not fully complete.

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 all three parameters are already documented in the schema. The description adds no new parameter-specific semantics beyond implying model_a_id and model_b_id are the two compared models, which is baseline value.

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 uses a specific verb ('Compare') and resource ('two AI models head-to-head'), and adds meaningful scope ('using accumulated pairwise benchmark battle history'). This clearly differentiates it from sibling tools like benchmark_get_leaderboard or benchmark_get_model_stats.

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 when to use it: when a direct head-to-head comparison of two models from prior duel history is needed. However, it does not explicitly state alternatives, exclusions, or when a different tool such as benchmark_start_duel or benchmark_get_leaderboard would be more appropriate.

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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