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. It discloses that the tool returns status and result, including an image URL upon completion, which is useful behavioral context. However, it doesn't mention other potential behaviors like error handling, rate limits, or what happens if the task is still processing. The description adds some value but leaves gaps for a tool with no annotation coverage.

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 appropriately sized and front-loaded, consisting of two concise sentences: the first states the core purpose, and the second specifies the return value. There is no wasted language, and every sentence earns its place by providing essential information without redundancy.

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 moderate complexity (single parameter, no output schema, no annotations), the description is partially complete. It covers the basic purpose and return value but lacks details on error cases, response formats beyond the image URL, or how to handle different task statuses. Without annotations or output schema, more context would be beneficial for full agent understanding.

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 input schema has 100% description coverage, with 'task_id' documented as 'Task UUID returned from generate_image'. The description doesn't add any additional parameter semantics beyond what the schema provides, such as format examples or constraints. Given the high schema coverage, the baseline score of 3 is appropriate as the schema handles the heavy lifting.

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: 'Get the status and result of a generation task' specifies the verb ('Get') and resource ('generation task'), and 'Returns image URL when completed' adds outcome details. However, it doesn't explicitly distinguish this from sibling tools like 'list_tasks' or 'generate_image', which would require mentioning it's for checking specific tasks rather than listing all tasks or creating new ones.

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 implies usage by referencing 'task_id returned from generate_image', suggesting it should be used after initiating a generation task. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'list_tasks' (for overview) or when not to use it (e.g., for non-generation tasks). The context is clear but lacks comprehensive alternatives or exclusions.

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