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How many credits a generation will cost

video_quote

Get exact cost quotes for AI video or image generation from Flow or Higgsfield before generating, so you can compare prices without spending credits.

Instructions

provider=flow: opens the Flow project, sets model and aspect, reads the cost Flow shows. provider=higgsfield: asks the Higgsfield CLI for the exact cost of model + prompt (images or videos). Generates nothing.

Input Schema

NameRequiredDescriptionDefault
countNo
modelNoflow: veo-lite, veo-fast, veo-quality, omni-flash. higgsfield: any job type, e.g. seedance_2_0, kling3_0, nano_banana_2veo-lite
aspectNo16:9
promptNohiggsfield: needed for an exact quote
providerNoflow

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.4.1

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses provider mechanics and the important fact that it generates nothing, but omits auth needs, whether opening/setting the Flow project persists state, rate limits, and return format.

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?

It is two sentences with no filler and front-loads the provider branches. The compact "provider=flow:" shorthand is efficient, though slightly terse, which keeps it from a 5.

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?

For a 5-param, no-annotation, no-output-schema tool, it covers the main provider branches and the no-generation guarantee. It still lacks return-value format/units, authentication expectations, and count semantics, leaving meaningful gaps.

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 40%, so the description must compensate. It adds useful semantics for provider, model, aspect, and prompt, especially the higgsfield prompt requirement for an exact quote, but does not explain the count parameter or clarify all aspect constraints.

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 states a specific purpose: quote credit cost for a generation, with provider-specific behavior, and explicitly says "Generates nothing," which separates it from generation siblings like video_generate. It does not explicitly contrast with usage_report or providers_list, so it is not a full 5.

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

Usage Guidelines3/5

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

It implies when to use it by provider and cost-quote purpose, but gives no explicit when/when-not guidance or alternatives such as video_generate or usage_report. An agent must infer that this is a pre-generation cost check.

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