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Look up operation prices

get_pricing
Read-only

Live credit cost of every operation: image tiers per model (generate_*, generate_pro_*, generate_gpt_*), restyle, cutouts, scans, and the per-second video rows (video_sec[ref][audio]; Veo is fixed video_veo_lites). Free. For a whole clip's price use generate_video with dry_run — it multiplies for you.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true, so the description needn't restate that. It goes beyond by specifying the pricing model details (per-second video rows, fixed Veo naming) and that it's free, which adds behavioral context that the annotations don't cover. It doesn't disclose return format, but for a zero-param read-only price lookup, the safety and cost implications are well handled.

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?

Dense, information-packed description with no filler. It front-loads the core purpose, then lists covered items, then adds the free and alternative-usage notes. Every sentence earns its place, and the structure is easy to scan.

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

Completeness5/5

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

For a zero-param read-only price lookups tool, the description covers all an agent needs: what operations are priced, the naming conventions for video rows, the cost (free), and the alternative for clip-level pricing. No output schema or params to compensate for, so completeness is high.

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

Parameters5/5

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

The tool has zero parameters, and schema coverage is 100% (nothing to cover). The description's detailed enumeration of the pricing dimensions (model tiers, video row patterns) substitutes for parameter documentation by telling the agent what to look for in the output. This is high value given there's no schema to lean on.

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?

States a specific verb ('get') and resource ('pricing'), and enumerates exactly what it covers: image tiers per model, restyle, cutouts, scans, and video rows. It clearly distinguishes itself from sibling tools like get_credits (a different concept) by specifying it's the live credit cost of every operation.

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

Usage Guidelines5/5

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

Explicitly says it's free, and provides a conditional alternative: for a whole clip's price, use generate_video with dry_run. This gives clear when-to-use and when-not-to-use guidance, and names the alternative tool, which is exactly what an agent needs to route correctly.

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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