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

No annotations are provided, so the description carries the full burden of behavioral disclosure and it carries none. It does not state how the tool receives input (especially puzzling given an empty parameter schema), what it returns, whether it is a pure read-only computation, or any error conditions. The post-colon phrase adds no behavioral information beyond what the name already implies.

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 description is short but not concise in a useful sense: the clause after the colon ('Ratio of content word') simply rephrases the tool name before it, so the only sentence earns no informational value. This is under-specification, not disciplined brevity.

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?

A text-analysis tool with zero parameters, no output schema, no annotations, and a seven-word tautological description is not callable by an agent with confidence. It fails to define the term 'content word,' explain how text is supplied, specify the ratio's numerator and denominator, or describe the return value. Adjacent to roughly 1,500 siblings including many overlapping text metrics, this definition is completely inadequate.

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?

The input schema has zero parameters with 100% coverage, so the rubric's baseline of 4 applies. The description adds nothing about parameters, but there are no parameters to document; the genuine gap—how text input reaches a 0-parameter tool—belongs to contextual completeness rather than this dimension.

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?

The description 'Content Word Ratio: Ratio of content word.' merely restates the tool name in slightly different words, making it a tautology rather than a definition. It never explains what a 'content word' is (e.g., lexical words like nouns/verbs/adjectives versus function words) and offers nothing to distinguish this from overlapping siblings such as x402-word-frequency, x402-keyword-density, x402-lexical-diversity, or x402-type-token-ratio.

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?

The description provides zero context about when to use this tool versus the many text-metric siblings in the same family. There is no mention of appropriate inputs, when not to use it, or any alternative tool that might be preferable for related tasks, leaving the agent to guess at routing.

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