Generate music from a text prompt with Lyria, optionally setting duration, model, and output path or filename for saving the resulting audio.
Generate music from a text prompt using Lyria. Check tool_list_available_models to verify Lyria is enabled in your project.
| Name | Required | Description | Default |
|---|---|---|---|
| params | Yes |
Changes observed during successful MCP inspections.
v3.3.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden, and it discloses almost nothing behavioral. It never says whether generation is synchronous or long-running, what gets returned (audio bytes vs. a file on disk), how output_path/output_filename interact, or any cost/rate limit. The only non-obvious behavior mentioned is the model-availability prerequisite.
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?
Two short sentences, front-loaded with the core action and followed by the prerequisite. Nothing is padded, though the brevity comes partly at the cost of the missing behavioral detail.
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?
With no annotations, no output schema, and a nested params object, the description should explain at minimum where generated audio goes and what a call returns. Neither is covered, leaving an agent unable to predict the side effects or result of invoking it.
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?
Schema description coverage is reported as 0% at the top level, and the description adds no parameter meaning at all — no mention of prompt, duration, model selection, or the output_path vs. output_filename relationship. It does not compensate for the coverage gap.
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?
States a specific verb and resource ('Generate music from a text prompt using Lyria'), which cleanly separates it from the sibling image/video/speech generators. It does not name or route against any specific alternative, so it stops short of a 5.
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?
Gives a concrete precondition: verify Lyria is enabled via tool_list_available_models before calling. That is real usage context, but there is no when-not-to-use guidance or comparison against sibling generators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.