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

There are no annotations, so the description carries the full burden of disclosure. It reveals significant behavioral traits: 'AI Studio run — dispatches to our AI workers (Modal)', 'Credits per run vary by model and file size', 'Files are deleted after processing', and 'auditable at mioffice.ai/account/tasks'. This exceeds typical transparency, covering execution model, cost variability, data lifecycle, and auditability.

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 moderately long but front-loaded with the core purpose and use cases. Each sentence adds relevant information (differentiation, pricing, file handling), and only a minor typo ('..') slightly detracts. The structure flows logically from function to usage to operational 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?

With no output schema, the description covers the tool's purpose, alternatives, use cases, cost model, and data deletion policy. However, it does not specify the output format (e.g., MP3/WAV) or how the text description is passed to the tool given the empty schema. These gaps are minor but reduce completeness for an agent evaluating invocation.

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 zero parameters, so the baseline is 4. The description mentions 'from text descriptions' but does not clarify how the text prompt is supplied (e.g., via conversation context or an implicit parameter). Since there are no schema-defined parameters, the description adds minimal parameter-related meaning, but the baseline for 0 params applies.

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 function: 'Generate royalty-free instrumental background tracks from text descriptions.' It specifies the verb (generate), resource (instrumental background tracks), and modality (from text descriptions). It also explicitly distinguishes from the sibling tool 'AI Song Generator' for songs with vocals, making it easy to differentiate.

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 explicit use cases: 'perfect for video, podcast, and ad backgrounds.' It gives a clear exclusion: 'No vocals' and points to 'AI Song Generator' as the alternative for songs with vocals. Additionally, it includes critical usage conditions like AI Studio credit requirements and which credit packs do not include AI Studio, guiding when this tool is appropriate.

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