extract_tfidf_keywords

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

No annotations are provided, so the description carries full burden. It only mentions 'computed from scratch' but fails to disclose behavioral traits such as computational cost, effects of single document, or required preprocessing. Minimal transparency beyond basic operation.

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 a single efficient sentence that conveys the core purpose without wasted words, meeting the conciseness criterion well.

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 an output schema present, the description need not explain return values. However, it lacks explanation of TF-IDF behavior for single document, output structure hints beyond schema, and preprocessing requirements. Adequate but with gaps.

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 0%, yet the description does not explain the parameters individually. It implies 'documents' usage but does not clarify 'top_n' or provide details about parameter meaning beyond the schema.

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 clearly states 'Extract keywords using TF-IDF computed from scratch', specifying a specific verb and resource. It distinguishes from sibling tools like 'extract_rake_keywords' by mentioning the TF-IDF algorithm and 'computed from scratch'.

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 context by saying 'Pass multiple docs for best results', implying when to use (multiple documents) and when not (single document). However, it does not explicitly mention alternatives like 'extract_rake_keywords'.

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