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

With no annotations and no output schema, the description carries the full behavioral burden, and it discloses nothing: not the return type (a numeric ratio), not the tokenization rules (whitespace vs. word-boundary vs. case sensitivity), and not whether punctuation/case are normalized. A caller cannot predict the result of a given input.

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 eight-word description is short but due to under-specification rather than tight editing; the second clause merely repeats the first. Brevity here costs the agent information rather than saving it effort.

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?

For a metric tool with two near-identical optional parameters, no annotations, and no output schema, the description should at minimum define the metric, state what it returns, and disambiguate the parameters. It does none of these, leaving the definition of the metric entirely absent.

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 coverage is 100%, and both parameters are documented, so the baseline of 3 applies. However, the description adds no meaning beyond the schema, and the two parameters ("text" and "input", described identically as "Text to process"/"Input to process") are near-duplicates whose relationship is never clarified.

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?

"Type Token Ratio: Ratio of type token" largely restates the tool name; the second half is circular rather than definitional. An agent that doesn't already know the linguistic metric cannot infer from this text that it computes unique words divided by total words, nor that it operates on a text input.

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 when-to-use guidance, no prerequisites, and no routing to or away from the many sibling text-metric tools (e.g. x402-lexical-diversity, x402-char-diversity, x402-hapax-legomena). The agent is left to guess when this metric is the right choice.

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