text_to_speech

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

With no annotations, the description covers key behavioral aspects: supports 23 languages, auto-plays audio on macOS, has a default voice. It does not mention cost, rate limits, or return format, but provides useful context beyond basic functionality.

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 front-loaded with use cases and key information. It is a single paragraph that could be slightly more concise but is well-organized and not overly verbose.

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 has 8 parameters and no schema descriptions, the description is incomplete. It covers the basic default usage but lacks details on advanced parameters and output schema. The presence of an output schema is not leveraged in the description.

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 0% with 8 parameters. The description only mentions 'text' and implies default settings for voice. It does not explain voice_id, language, output_format, model, speed, pitch_shift, or style, leaving significant gaps for parameter usage.

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 generates natural-sounding speech from text and lists specific use cases like reading aloud, creating narration, or voiceover. It distinguishes itself from sibling tools by explicitly mentioning that search_voice should only be called for browsing voices.

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?

Provides explicit guidance on when to use the tool: when the user wants to hear text read aloud, create narration, etc. It also gives a clear exclusion: only call search_voice if the user explicitly asks to change or browse voices.

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