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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: it returns a task ID for async tracking (implying asynchronous operation), states the cost ($0.68), and provides constraints like character recommendations (200-500 chars) and format instructions. It does not cover aspects like rate limits or error handling, but offers substantial context beyond basic functionality.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and appropriately sized, with key information front-loaded (purpose, cost, async tracking). It uses bullet-like formatting for instructions and includes an example, which aids clarity. Some sentences could be more concise (e.g., the cost note is brief but clear), but overall, it avoids unnecessary verbosity and each sentence serves a purpose.

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

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

Given the tool's complexity (5 parameters, async operation, cost implications) and no output schema, the description is moderately complete. It covers the purpose, usage, cost, and async nature, but lacks details on output (e.g., what the task ID leads to, error cases, or links to sibling tools like get_task). With no annotations and no output schema, more context on behavioral outcomes would improve completeness.

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

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

The schema description coverage is 100%, so the baseline score is 3. The description adds some value by emphasizing the prompt parameter with an example and instructions, but it does not provide significant additional semantics for other parameters like instrumental, duration, loudness_preset, or audio_format beyond what the schema already documents. The description compensates minimally for the high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Generate AI music from text description using VAP (Suno V5).' It specifies the verb ('Generate'), resource ('AI music'), and technology ('VAP (Suno V5)'), distinguishing it from sibling tools like generate_image or generate_video. The description is specific and unambiguous about what the tool does.

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

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

The description provides clear context on when to use this tool by specifying it's for generating music from text descriptions, with an example prompt. It includes important usage instructions like 'Send ONLY the music description' and what to include in the description. However, it does not explicitly state when not to use it or compare it to alternatives like estimate_music_cost, which would be needed for a score of 5.

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