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 only offers a category tag '[inference]' and the task name; it does not disclose determinism, rate limits, output format, or whether max_keywords is a hard limit, leaving behavioral traits entirely 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?

The description is a single fragment, which is concise but under-specified. It is front-loaded but lacks any structure that would help an agent understand scope or behavior.

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, no output schema, and 0% parameter coverage, the description is far too sparse. It omits return format, keyword selection criteria, and how max_keywords affects output, leaving critical gaps for an agent.

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% and the description adds no information about the two parameters (text, max_keywords). It does not explain what max_keywords does, its default, or accepted range, so it fails to compensate for the schema gap.

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 'Keyword extraction' – a specific task on text, distinct from siblings like text_sentiment and text_summarize. However, it lacks an explicit verb and does not name alternatives, so it is clear but not fully 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 guidance on when to use this tool versus text_summarize or text_sentiment, nor any exclusions or prerequisites. The name implies a use case, but the description provides no explicit context.

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