wordfreq_analyse

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 does not state whether counting happens on tokens/whitespace, whether stop-word removal applies, how ties are resolved, or what the response shape looks like. The mention of 'top words' hints at sorting, but the default behavior remains opaque.

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?

A single efficient sentence with the verb and outcome front-loaded. It is adequately sized, though 'returning counts and top words' slightly overlaps the parameter documentation.

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?

With no annotations and no output schema, the description should do more to describe return structure and counting semantics. It covers the high-level purpose but leaves the agent without enough behavioral context to call the tool confidently, especially given the near-duplicate sibling.

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 description coverage is 100%, so the schema already documents top, text, and case_sensitive including defaults. The description adds essentially nothing beyond 'returning counts and top words', which is baseline-level for fully documented parameters.

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 ('Analyse') plus resource ('word frequencies in text') and names what it returns ('counts and top words'). It distinguishes itself from siblings like word_count and frequency_analyse by narrowing to word frequency, though the near-identical sibling frequency_analyse is not explicitly differentiated.

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 mention of alternatives. The presence of a very similar sibling (frequency_analyse) makes this omission meaningful – the agent has no stated basis for choosing between them.

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