text_to_speech

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

With no annotations, the description carries the full burden and does so thoroughly: it discloses provider fallback order, that the local fallback always emits .wav regardless of output_format, that voice is ignored on the local tier, and exact prerequisite setup (local-tts extra and espeak-ng).

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 content is front-loaded with the one-line summary, followed by dense but relevant provider/fallback details and an Args section. Every sentence adds operational value with no filler.

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?

For a tool with no annotations and no parameter descriptions, the description covers provider selection, key requirements, output-directory behavior, and per-parameter semantics. An agent has enough information to invoke it correctly without inspecting sibling tools or external docs.

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 coverage is 0%, but the description manually documents all three parameters: text, voice (with example and fallback behavior), and output_format (with allowed values and the caveat that it is only honored on Groq). This fully compensates for the empty schema.

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 opens with a specific verb and resource: 'Convert text to speech, saved to output/.' This makes the tool's function immediately clear and distinguishes it from siblings such as speech_to_text (reverse direction) and list_voices/check_provider_health (support tools).

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?

It clearly states the primary purpose and the conditions under which each provider path is used: Groq first when available and the key is set, local fallback otherwise. It doesn't explicitly name when-not-to-use cases, but no sibling tool competes for this task, so clearer context would be marginal.

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