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 richly: 1-2s latency, output format per language (MP3/WAV), 24-hour URL validity, size/base64 return, character limit, and the billing model. Crucially it discloses that payment is required via x402 USDC at $0.01/call with no API key, and that billing only occurs on delivery – exactly the behavioral facts an agent needs before invoking.

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?

Front-loads the core purpose and packs a lot of useful detail into a tight paragraph. It is dense but nearly every clause (languages, engines, formats, cost) earns its place; a small deduction for the run-on pricing sentence.

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?

Despite no output schema and no annotations, the description specifies the return payload (hosted URL, validity window, size, optional base64), cost, and payment prerequisite – everything needed to call and interpret the result correctly.

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 100%, so lang, text, and inline are already documented in the schema; the description only restates text length and the inline/base64 behavior. Baseline 3 is appropriate since the schema does the heavy lifting.

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?

States a specific verb+resource (text-to-speech) plus the exact languages and the underlying engines (Aura-2 for en/es, MeloTTS for the rest). It is immediately distinguishable from the reverse-direction sibling ai_transcribe.

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?

Usage context is implied by the capability and the 2000-character/language constraints, but the description never compares against alternatives or states when-not to use it (e.g., vs ai_transcribe or ai_translate). The inline=true note is parameter guidance, not tool-selection guidance.

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