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

With no annotations, the description carries the full burden. It usefully discloses case-insensitive matching, the 0-to-1 output range, and the pay-per-call model ('5 free trial calls per signed wallet'), which is real behavioral context. However, it omits tokenization rules for multi-word keywords, behavior on empty text or missing terms, and error output.

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 definition is front-loaded and tight: the computation comes first, then inputs, then output range, then pricing. The emoji promotional line is the only non-essential element, and it is at least kept to the end.

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 simple read-only calculator with no output schema, the description covers the result range and the comparison rule, which is most of what is needed. It falls short on disambiguating the four overlapping input fields and on any error/edge-case behavior, which matters given zero annotation coverage.

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 0% and four parameters are declared (term, text, input, keyword) with an unstated required list. The description mentions only 'text' and 'keyword' and does not explain whether 'term' and 'input' are aliases or alternatives, leaving half the parameters ambiguous in both schema and description.

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-like operation and resource: the share of words in a text equal to a given keyword, computed case-insensitively. That is precise enough to separate it from x402-word-frequency and x402-keyword-extract by inference, but it never names or contrasts those siblings explicitly.

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?

There is no when-to-use or when-not-to-use guidance and no reference to the many text-analysis siblings (word-density, keywords, word-frequency, lexical-diversity). The agent must infer applicability purely from the one-line definition.

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