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vapagentmedia

VAP Media · Unified MCP Server for AI Agents (Flux · Veo · Suno)

estimate_cost

Calculate image generation costs before processing to manage budgets. Estimates pricing based on quality settings and output quantity.

Instructions

Estimate the cost of an image generation before executing. Cost: $0.18

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qualityNoGeneration quality levelstandard
num_outputsNoNumber of images to generate
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the tool estimates cost without execution, which is useful, but doesn't cover aspects like whether it's a read-only operation, requires authentication, has rate limits, or what the output format is. The cost mention adds some context but is incomplete.

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?

The description is very concise with two short sentences, front-loading the core purpose. However, the standalone cost figure ('Cost: $0.18') feels tacked on without context, slightly reducing efficiency. Overall, it's brief but could be more integrated.

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

Completeness2/5

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

Given no annotations and no output schema, the description is incomplete for a cost estimation tool. It mentions a fixed cost but doesn't explain how parameters affect it, what the return value looks like, or error conditions. For a tool with two parameters and financial implications, more detail is needed to be fully helpful.

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 fully documents parameters. The description adds no parameter-specific information beyond implying cost calculation, which aligns with the schema's purpose but doesn't provide additional syntax, format details, or examples. Baseline 3 is appropriate as the schema handles parameter documentation.

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 clearly states the tool's purpose: estimating cost before image generation execution. It specifies the action ('estimate'), resource ('cost'), and context ('image generation'), distinguishing it from siblings like generate_image. However, it doesn't explicitly differentiate from estimate_music_cost or estimate_video_cost beyond mentioning 'image'.

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?

The description implies usage context ('before executing') and mentions a specific cost, suggesting when to use it for budgeting. However, it lacks explicit guidance on when to choose this over alternatives like generate_image directly or other estimate tools, and doesn't mention prerequisites or exclusions.

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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