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word_frequency

Calculate word frequency from any text input. Identify the most common terms and their counts for content analysis.

Instructions

word frequency — Other Utilities tool. Costs $0.001 USDC via x402.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsNoTool parameters as JSON object
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It discloses a financial cost ($0.001 USDC via x402), which is a useful behavioral trait, but gives no information about safety, side effects, or whether it requires authentication. The description is minimal beyond the cost, leaving key behaviors undisclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately brief and front-loaded, with two short segments. However, it is under-specified rather than effectively concise; every sentence states trivial information (name and cost). It is not bloated, but it fails to provide essential context within its brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the generic schema, lack of output schema, and many sibling tools, the description is highly incomplete. It leaves an agent to infer what the tool does, what parameters to pass, and what to expect in return. The only concrete additional context is the cost, which is insufficient for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema contains a single 'params' object described only as 'Tool parameters as JSON object,' which provides no specific parameter names or semantics. The tool description does not compensate by explaining expected fields (e.g., 'text'). While schema coverage appears high, the description is merely a placeholder and offers no actionable parameter meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'word frequency — Other Utilities tool' merely restates the tool name and places it in a broad category. It lacks a verb or explicit function, such as 'Counts word occurrences in text,' and does not distinguish it from sibling tools like word_count or keyword_density. This is closer to a tautology than a clear purpose statement.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives. The description does not mention the type of input (e.g., text) nor compare it to other text-analysis utilities. An agent receives no context for tool selection.

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

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