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runapi-ai

@runapi.ai/gemini-omni-mcp

by runapi-ai

check_pricing

Look up RunAPI pricing for the gemini-omni model line.

Instructions

Look up RunAPI pricing for the gemini-omni model line.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel slug. Defaults to the line's primary model.
actionNoEndpoint name. Defaults to the endpoint that offers the model.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.2.2
    • changedInput schema / properties / model / enum
      Previous value: -[
      -  "gemini-omni-audio",
      -  "gemini-omni-character",
      -  "gemini-omni-flash-preview",
      -  "gemini-omni-text-to-video"
      -]New value: +[
      +  "gemini-omni-audio",
      +  "gemini-omni-character",
      +  "gemini-omni-flash-1-1",
      +  "gemini-omni-flash-preview",
      +  "gemini-omni-text-to-video"
      +]
  2. Addedv0.2.1
  3. Removedv0.2.0
  4. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states the operation is a 'look up,' suggesting it is read-only, but it does not disclose any side effects, authentication requirements, rate limits, return format, or whether results are cached. The agent gains no explicit behavioral safety guarantees.

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?

The description is a single, direct sentence that front-loads the core purpose. There is no redundant wording and every word earns its place, making it easy for an agent to quickly grasp the tool's function.

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?

The tool is relatively simple (two optional params, no output schema), but the description does not explain what the response looks like, which is essential since no output schema exists. It also lacks any mention of how the result might be used in conjunction with sibling tools. It is adequate for a basic read, but incomplete for operational use.

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 100%, with both parameters (model and action) having enum descriptions. The tool description adds no information beyond what the schema already provides, so the baseline 3 is appropriate—it neither harms nor helps beyond the schema.

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 states a specific action ('Look up'), a specific resource ('RunAPI pricing'), and a specific scope ('gemini-omni model line'). It clearly differentiates from siblings like create_audio and text_to_video, which perform content creation, while check_pricing is a read-only query.

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?

The description provides no guidance on when to use this tool versus the named siblings (e.g., when to query pricing before creating a task). It does not mention any conditions, exclusions, or prerequisites. The context is only implied by the tool name and purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.