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get llm pricing

get_llm_pricing
Read-only

LLM model pricing (OpenRouter) (source: OpenRouter models API). Full current feed, refreshed daily. Requires API key.

Input Schema

NameRequiredDescriptionDefault
qNoCase-insensitive full-text filter
limitNo
sinceNoISO date; only rows created/updated on or after
offsetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds two genuinely useful behavioral facts beyond the annotations: an API key is required, and the feed is refreshed daily (so results may be up to a day stale). It still says nothing about pagination behavior or result size, so it is adequate rather than rich.

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?

Three compact fragments, front-loaded with the resource and source, with no filler. The parenthetical '(source: OpenRouter models API)' is slightly redundant with the preceding parenthetical, but the total length is well matched to the tool's simplicity.

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 has to carry the return-value burden, and 'Full current feed' only gestures at what comes back (pricing records). For a four-parameter, read-only list tool whose annotations and schema cover safety and arguments, this is minimally sufficient but leaves return format and paging unspecified.

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 50%: 'q' and 'since' are documented in the schema, while 'limit' and 'offset' are self-explanatory from their defaults and bounds. The description contributes no parameter meaning at all, so it neither compensates for nor exceeds the schema — baseline 3 for a mostly self-documenting parameter set.

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 the resource precisely (LLM model pricing from the OpenRouter models API) and states the scope is the full current feed. It is clear what the tool returns, but it never distinguishes itself from the sibling get_ai_pricing, so an agent cannot tell which pricing tool applies without opening both schemas.

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 / when-not-to-use guidance and no mention of alternatives. 'Full current feed, refreshed daily' describes the data, not the conditions under which an agent should call this instead of get_ai_pricing or a cached lookup.

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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