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Quote Generation

quote_generation
Read-onlyIdempotent

Exact credit cost of a generate_image, edit_image or generate_video call before making it, with the caller's balance and plan eligibility. Use it whenever price or budget comes up instead of estimating. Free; nothing is reserved or started.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYesThe call being priced
modelNoModel id as that tool accepts it; omitted means the tool's default
durationNogenerate_video only: seconds
resolutionNogenerate_video only
with_imageNogenerate_video only: true when an image_url will be animated

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses that the call is free, reserves nothing, and starts nothing. This is important behavioral context for a pricing tool and is not redundant with the annotations.

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?

Three short sentences each carry distinct value: what it returns, when to use it, and its side-effect profile. The key purpose is front-loaded.

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 quote tool with no output schema, it describes the returned values (cost, balance, plan eligibility), the applicable tools, and the safety profile. Parameter constraints are fully covered by the schema, and annotations cover side-effect safety.

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%, so the schema already explains all five parameters. The description adds no parameter-level semantics beyond listing the same tool names in the enum.

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 function: returning the exact credit cost for a specified generation call before execution, plus balance and plan eligibility. Naming generate_image, edit_image, and generate_video as the priced operations differentiates it from the sibling generation and balance tools.

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

Usage Guidelines4/5

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

It explicitly tells the agent to use this tool whenever price or budget comes up rather than estimating. It does not, however, name alternative tools or exclusion conditions, such as when to use get_credits for balance-only queries.

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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TDQS

A4.4/5.0
Disambiguation5/5

Each tool maps cleanly to a distinct action: generate new media, edit media, retrieve by ID, list history, view models, check credits, and quote a potential cost. Even check_generation and list_generations are clearly separated by lookup-by-id versus listing. No two tools appear to do the same thing.

Naming Consistency5/5

Every tool follows the same verb_noun snake_case pattern, such as generate_image, list_models, and quote_generation. The verbs are descriptive and consistently chosen for each operation. This makes the tool surface highly predictable for an agent.

Tool Count5/5

Eight tools is well-scoped for a media generation server covering image generation, video generation, editing, history retrieval, model discovery, and credit management. Each tool serves a clear purpose without redundancy or feature bloat.

Completeness5/5

The tool set covers the full generation lifecycle: creating images, creating videos, editing images, checking generation status, listing past results, inspecting models and costs, quoting prices, and checking credits. There are no obvious dead ends or missing core operations for the stated domain.

Resources