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Glama

operant-mcp

by io.github.saagpatel

Inspect two retained profiles

compare_models
Read-only

Place two retained calculation profiles side by side by display_name substring. Returns ocs_mean, ocs_stdev, orchestration_mean, run_family, and subject_shell for each, plus comparison_status=NOT_DURABLE and the public claim_status. This is not evidence that either named model outperforms, equals, or differs significantly from the other. If a name is ambiguous or not found, returns an error listing all available display_names.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_aYesDisplay name (or substring) of the first model
model_bYesDisplay name (or substring) of the second model

Schema Changelog

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

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Discloses specific return fields, error behavior for ambiguous names, and a crucial caveat about the comparison not indicating statistical significance. The readOnlyHint from annotations is consistent, and the description adds detailed behavioral context beyond annotations.

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?

Two well-structured sentences: first sentence states purpose and returns, second sentence provides usage caveat and error handling. No redundant information, every sentence adds value.

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?

Given no output schema, the description fully covers what the tool does, what it returns, error conditions, and important limitations. It is self-contained and sufficient for an agent to understand and invoke the tool correctly.

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 input schema already describes the parameters with 'Display name (or substring) of the first/second model.' The description only restates 'by display_name substring' without adding new semantics, and since schema coverage is 100%, a score 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 the tool's purpose: 'Place two retained calculation profiles side by side by display_name substring.' It specifies the exact fields returned and differentiates from sibling tools like get_case or list_cases by focusing on comparison.

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?

Provides guidance on ambiguous names (returns error listing all available display_names) and cautions that comparison_status=NOT_DURABLE means it's not evidence of outperformance. However, it does not explicitly state when to use this tool versus alternatives like get_results or list_cases.

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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TDQS

A4.5/5.0
Disambiguation5/5

Each tool has a distinct purpose: compare_models compares two profiles, get_case retrieves a full case, get_methodology explains the benchmark design, get_results returns calculation profiles, and list_cases lists metadata. No overlap or ambiguity.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (compare_models, get_case, get_methodology, get_results, list_cases) using underscores and imperative verbs.

Tool Count5/5

5 tools is well-scoped for a benchmark analysis server. Each tool covers a necessary function without being excessive or lacking.

Completeness5/5

The tool set covers the full lifecycle of exploring the benchmark: listing cases, retrieving details, understanding methodology, accessing results, and comparing models. No obvious gaps given the read-only purpose.

Resources