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

Annotations only declare safety flags, so the description's cost disclosure is real added value: $0.001 USDC on Base, x402, and critically 'per successful call', which tells the agent failed calls are not billed. It does not explain error behavior, latency, or input size limits, but it goes meaningfully beyond the structured fields.

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?

Three sentences, front-loaded with capabilities, then use case, then the billing sentence that a paid tool needs. No filler. Slightly long enumeration of metrics, but each item maps to a real returned statistic rather than padding.

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?

No output schema exists, and the description compensates by enumerating the returned statistics, so an agent knows what it gets back. The payment rail and language restriction are covered. Missing only failure modes and limits, which is acceptable for a single-parameter read-style tool.

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?

One parameter at 100% schema coverage, whose schema text is only 'The text', so the baseline would be 3. The description adds a genuine semantic constraint the schema lacks ('English text'), which changes how the agent should populate the parameter - i.e. do not pass arbitrary-language drafts.

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?

Specific verb+resource with an explicit inventory of what is computed (character/word/sentence/paragraph counts, reading and speaking time, Flesch reading-ease and grade level) and a bounded domain ('English text'). No sibling among the large list does text metrics (text_diff, text_extract, html_to-text are all distinct), so differentiation is implicit but 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?

'Use to check the length and readability of a draft' supplies one concrete use case, which is more than nothing. However, it names no alternatives and no when-not conditions (e.g. non-English input, or pairing with an ai_rewrite call after the draft fails a readability bar), leaving routing largely to inference.

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