get_generationRetrieve the current state of a music generation task by id. Status is pending, ready, or failed; audio URLs appear on ready.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Generation task id, returned by generate_music. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral detail beyond annotations: the possible statuses (pending, ready, failed) and that audio URLs only appear on 'ready'. This helps the agent interpret the response and understand the lifecycle. It doesn't describe error responses or behavior for unknown ids, but that is a minor gap.
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 concise sentences convey the purpose and key behavioral details without fluff. Every word adds value: the verb, the resource, the status set, and the audio URL note. Front-loaded with the core action and then elaborates efficiently.
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 simplicity (one parameter, no output schema), the description is complete. It covers what the tool does, the status values, and when audio URLs appear. Annotations handle safety hints, and sibling names provide context for the tool's role. No critical information is missing.
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 100%; the parameter 'id' is already described as 'Generation task id, returned by generate_music.' The description adds little beyond the schema, only implicitly referencing 'by id'. Therefore, the baseline of 3 is appropriate since the schema handles the parameter meaning.
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 verb 'Retrieve' and the resource 'current state of a music generation task by id'. It also differentiates from siblings: generate_music creates tasks, list_models lists models, while this tool fetches task state. The mention of statuses and audio URLs makes the function unambiguous.
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 context: after generating music with generate_music, one polls this tool with the returned id to check status. It explains what statuses mean and that audio URLs appear when ready, giving clear context for when to call it. However, it does not explicitly name alternatives or state when not to use it, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool addresses a distinct stage of the workflow: list_models for discovery, generate_music for task creation, and get_generation for status/results. There is no overlap between them.
All tool names follow the same verb_noun pattern in lowercase snake_case: generate_music, get_generation, list_models. This is perfectly consistent and predictable.
Three tools is well-scoped for a music generation API. Each tool has a clear, necessary role, and none are redundant or missing.
The tool surface covers the complete user workflow: list available models, create a generation task, and retrieve the finished output. No obvious gaps exist.