gemini-media-mcp

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 mentions the technology (Lyria models) and supported features but lacks critical details such as rate limits, authentication requirements, output format (implied by output schema but not described), or potential side effects like resource consumption. This leaves significant gaps for an AI agent to understand the tool's behavior.

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 a single, efficient sentence that front-loads the core purpose and lists key features. It avoids redundancy and waste, though it could be slightly more structured by separating core functionality from feature details.

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 (music generation with multiple features), no annotations, and an output schema (which reduces the need to describe return values), the description is moderately complete. It covers the basic purpose and supported features but lacks behavioral context and usage guidelines, making it adequate but with clear gaps for effective tool selection.

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 input schema already documents both parameters thoroughly. The description repeats the prompt's supported features verbatim from the schema, adding no new semantic information. It doesn't explain the model parameter's implications beyond what's in the schema, resulting in minimal added value.

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 music from a text prompt using Google's Lyria models.' It specifies the verb (generate), resource (music), and technology (Lyria models). However, it doesn't explicitly distinguish this from sibling tools like 'generate_audio' or 'generate_video', which might have overlapping functionality.

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 no guidance on when to use this tool versus alternatives like 'generate_audio' or other media generation tools. It lists supported features but doesn't indicate prerequisites, constraints, or typical use cases beyond the basic functionality.

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