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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=false and openWorldHint=true. The description adds genuinely new context: it confirms nothing is changed, discloses the $0.01 x402/card-key cost, the first-25-free allowance, that failed calls are free, and that repeats are charged — consistent with idempotentHint=false.

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 the capability list, then usage, then example, then cost. Every clause carries information, though the pricing sentence is dense and the inline example is slightly clunky.

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, so the description must convey return values — and it lists every metric produced (counts, reading/speaking time, Flesch ease, grade level). Combined with the cost and read-only disclosures, an agent has what it needs to call it 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?

Single required parameter at 100% schema coverage, so the schema baseline applies. The description still adds value by stating the text must be English (relevant because Flesch scoring is language-specific) and by supplying a concrete example value.

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?

Names a specific verb set and resource: counts characters, words, sentences, paragraphs, estimates reading/speaking time, and computes Flesch reading-ease and grade level. The scope is precisely bounded to English text, which separates it from generic stats siblings like math_stats or pack_text_analysis.

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" gives clear situational context, and the worked example anchors the input. It stops short of naming an alternative (e.g., text_keyword_density for keyword analysis), so it is clear but not fully routing.

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