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

Annotations only cover safety (readOnlyHint) and open-world reach, but the description adds substantial non-obvious behavior: the exact cost ($0.002 USDC per successful call), the x402 payment rails (Base/Solana/Arc), and that failed calls are not charged. It also discloses reliability caveats – Flesch-Kincaid is a code estimate and model judgements are not measurements – which meaningfully shape how results should be trusted.

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-loaded with what it does, then caveats, then pricing – a logical order with no filler. Dense but every clause (limits, estimate disclaimer, pricing) carries information an agent needs, though it is on the longer side for a single-parameter tool.

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 an output schema present, return-value details needn't be explained, and the description still covers input limits, output fields, reliability caveats, and the full payment model. The one gap is the absence of any guidance distinguishing it from the sentiment/readability siblings.

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% and there is a single required parameter whose schema already documents the 10,000-character limit. The description restates the same limit without adding format, encoding, or language semantics, so 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?

States a specific verb+resource ('Tone analysis of a text') and enumerates the concrete outputs (formality 0-1, sentiment, emotion scores, tone labels, suggestions), so the agent knows exactly what it produces. It does not, however, distinguish itself from overlapping siblings like sentiment, text_readability, or moderate.

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?

No explicit guidance on when to use this versus alternatives such as sentiment (sentiment scoring) or text_readability (reading level). The only usage-adjacent note is the 10,000-character cap, which is a constraint rather than routing advice.

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