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vapagentmedia

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

estimate_music_cost

Calculate music generation costs based on duration and format for AI agents using Suno V5, providing deterministic pricing estimates.

Instructions

Estimate the cost of music generation. Cost: $0.68 (Suno V5)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
durationNoMusic duration in seconds
audio_formatNoOutput format. WAV adds +$0.10mp3
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states a cost but doesn't explain if this is per-use, includes taxes, requires authentication, has rate limits, or what the output format is. For a cost estimation tool with zero annotation coverage, this leaves critical behavioral traits unspecified.

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 extremely concise—just one sentence with no wasted words. It front-loads the core purpose and includes essential cost information efficiently. Every element earns its place, making it easy for an agent to parse quickly.

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?

For a cost estimation tool with no annotations and no output schema, the description is incomplete. It doesn't specify what the estimate returns (e.g., total cost, breakdown), how parameters affect the calculation beyond a vague format note, or any error conditions. Given the complexity of pricing and lack of structured data, more context is needed for effective 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?

The input schema has 100% description coverage, with clear documentation for both parameters (duration and audio_format). The description adds minimal value beyond the schema: it mentions a base cost and implies format affects price ('WAV adds +$0.10'), but doesn't fully explain how parameters influence the estimate. Given high schema coverage, a baseline score of 3 is appropriate.

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: 'Estimate the cost of music generation.' It specifies the verb ('estimate') and resource ('cost of music generation'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'estimate_cost' or 'estimate_video_cost', which prevents a perfect score.

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 alternatives. It mentions a specific cost ('$0.68 (Suno V5)') but doesn't clarify if this is a fixed rate, how it relates to parameters, or when to choose this over 'estimate_cost' or 'estimate_video_cost'. Without usage context or exclusions, the agent lacks direction.

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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