generate_speech

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'multi-role conversations and audio merging,' which adds some context about features, but fails to cover critical aspects like rate limits, authentication needs, output format, or error handling. For a tool with no annotations, this is insufficient.

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 highly concise and front-loaded, consisting of two efficient sentences that directly state the tool's purpose and key features. Every sentence adds value without redundancy, making it easy for an AI agent to parse quickly.

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 complexity of audio generation, lack of annotations, no output schema, and low schema coverage, the description is incomplete. It omits details on output format, error conditions, performance limits, and parameter usage, leaving significant gaps for an AI agent to operate effectively.

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%, so the description must compensate for undocumented parameters. It implies 'items' relate to text inputs and 'merge_output' controls audio merging, but does not explain parameter meanings, formats, or constraints. This leaves key input details ambiguous, failing to adequately supplement the 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 clearly states the tool's purpose: 'Generate speech audio from text using Microsoft Edge TTS.' It specifies the action (generate), resource (speech audio), and technology (Microsoft Edge TTS). However, without sibling tools, it cannot demonstrate differentiation from alternatives, preventing a perfect score.

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 no guidance on when to use this tool versus alternatives. It mentions 'Supports multi-role conversations and audio merging,' which hints at capabilities but does not specify use cases, prerequisites, or exclusions. This lack of explicit context limits its utility for an AI agent.

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