synthesize_speech

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

No annotations are provided, so the description must fully disclose behavior. However, it only states the basic conversion function and language/voice support, without mentioning output format, latency, quotas, or any side effects. This is a significant transparency gap, so a score of 2 is given.

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 two sentences with no redundancy, front-loading the core action ('Convert text to speech') and adding a concise capability note.

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 and no annotations, the description is moderately complete: it explains the core function and the schema covers all parameters, but it omits any explanation of the return format or audio output behavior. This limits completeness, so a score of 3 is justified.

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?

All three parameters are fully described in the schema (100% coverage), so the description doesn't need to add parameter details. The mention of language/voice support in the description merely echoes the schema and adds no new semantic information. Baseline 3 is appropriate.

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 uses the specific verb 'convert' and clearly identifies the resource ('text to speech') and implementation ('Microsoft Azure Speech Services'). It also mentions multi-language and voice support, making the tool's purpose 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?

There are no sibling tools, so explicit alternatives aren't required. The description provides clear context for when to use the tool (when text-to-speech synthesis is needed) but doesn't include exclusions or prerequisites, so a score of 4 is appropriate.

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