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LLM Cutover

List priced models

list_models
Read-only

Current models with $/1M token prices and effort levels, usable as current.model.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior3/5

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

readOnlyHint=true already declares the safety profile, so the description only needs to add substance, and it does disclose the two payload categories (per-1M-token prices, effort levels) and that entries are consumable as current.model. It does not describe the return shape (array vs map), whether prices are live or cached, or whether any auth is required; with no output schema, that is a modest gap.

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?

A single clause with zero filler; the most actionable detail ('usable as current.model') is placed last for emphasis and every word carries information. Nothing is repeated from the schema or annotations.

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?

For a zero-parameter, read-only listing tool with no output schema and an unrelated sibling, the description covers intent, payload, and consumption well enough to call it correctly. Only the absence of any return-shape or freshness note keeps it from being fully complete.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline applies. The mention of '$/1M token' units and 'effort levels' adds useful semantic context about what domain values mean even though there are no inputs.

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?

Names the resource precisely ('Current models') and the payload it carries ('$/1M token prices and effort levels'), which is enough for an agent to know this is a model catalog with pricing. It is a noun phrase rather than a verb+resource sentence, and it never explicitly says 'list', though the plural and the title make the operation unambiguous. The sibling (run_cutover_audit) is unrelated, so no differentiation is needed.

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 clause 'usable as current.model' implicitly tells the agent this is how you discover valid values for a configuration field before setting it, which is a real usage cue. There is no explicit when-to-use or when-not statement, and no mention of prerequisites or alternatives.

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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