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TANDIU AI infrastructure data

Cheapest model at a benchmark score

cheapest_model_for_score
Read-onlyIdempotent

Cheapest models whose benchmark score meets a threshold (absolute or percent of the best score).

Input Schema

NameRequiredDescriptionDefault
limitNo
metricNo
countryNo
min_scoreNo
min_percent_of_topNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and a closed-world scope, so the safety profile is covered. The description adds that the threshold can be absolute or relative to the best score, which is useful, but it omits result ordering, tie-breaking, defaults, and behavior when no parameters are supplied.

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?

A single front-loaded sentence with no filler or repetition. It is tight, though its brevity is partly the cause of the missing parameter and usage detail rather than a sign of completeness.

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?

For a five-parameter tool with zero required params, no output schema, and no param descriptions, the definition is too thin. An agent cannot tell what happens with an empty call, which metric is default, or how limit and country constrain results.

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

Parameters2/5

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 only clarifies the two threshold parameters (absolute vs percent-of-top). The limit, metric (aa_index vs livebench), and country parameters are left entirely unexplained, along with which of the two threshold params is mutually exclusive.

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?

The description names a specific verb+resource: it returns the cheapest models meeting a benchmark score threshold, which is distinct from siblings like list_llm_prices or get_price_index. It does not, however, explicitly differentiate itself from those price-oriented siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance, no statement of prerequisites, and no mention of alternatives such as list_llm_prices for raw pricing or estimate_* tools for cost projections. Usage must be inferred entirely from the name and one-line description.

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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