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Search models

search_models
Read-only

Searches the catalogue of AI models and returns their current prices, with a confidence level and the sources backing each price.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNoFree text matched against name and id.
providerNoRestrict to one provider slug, e.g. `openai`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

readOnlyHint=true already establishes the safety profile, so the description only needs to add context. It does add something meaningful — that results are decorated with a confidence level and backing sources — but says nothing about pagination, ordering, total result counts, or how the default limit of 20 behaves.

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 well-formed sentence with no filler, front-loading the action and resource before the return characteristics. Every clause earns its place.

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

Completeness3/5

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

With no output schema, the description is the only source of return-value information, and it covers that at a high level (prices, confidence, sources). It leaves out result ordering, truncation behavior, and how to handle a zero-match search — gaps that matter for a search tool.

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 coverage is 67%: query and provider are self-documenting, and limit carries bounds and a default even without prose. The description contributes no parameter-level detail (matching behavior, slug format, limit semantics), so the baseline 3 is appropriate.

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?

States a specific verb and resource ('Searches the catalogue of AI models') plus what comes back ('current prices, with a confidence level and the sources'). It does not distinguish itself from close siblings like get_model_price or compare_models, so an agent must infer the split between a catalogue search and a single-model lookup.

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 explicit when-to-use statement, no exclusions, and no named alternative. The description never tells the agent to prefer search_models over get_model_price for a known model, or when compare_models is the better call.

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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