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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is covered without the description. The description does add useful non-schema context by disclosing a 2-credit cost and the array-of-words return shape. It does not disclose whether unrecognized words are skipped, whether the category match is case-sensitive, or what happens on invalid categories, so it stays at an adequate 3.

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?

Three short sentences with the tool purpose first, the invocation pattern second, and the cost last, so nothing blocks an agent scanning for the tool's purpose. The opening phrase 'Parts Of Speech: Parts Of Speech extracts...' restates the title and could be trimmed, which keeps this from a 5.

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 two-parameter extraction tool with full schema coverage, annotations, and an output schema, the description covers purpose, invocation, and cost. The one meaningful gap is that the accepted part-of-speech values are only hinted at by example rather than enumerated, which a short list could have closed.

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 100%, so the schema already documents both parameters, and the 3 baseline applies. The description does add a little meaning by naming candidate categories (nouns, verbs, adjectives) even though the 'partofspeech' parameter has no enum and only a single-string example, but the 'like' hedge leaves the full set of accepted values ambiguous and does not clarify case sensitivity or defaults beyond what the schema says.

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 uses a specific verb and resource: extracts words from text filtered by grammatical category (nouns, verbs, adjectives), and says the output is an array of matching words. That is clear enough to distinguish it from siblings like TextLemmatizer or KeywordExtractor, but those alternatives are never named, so the differentiation is left to the agent.

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 sentence 'Pass any text passage and a category to receive an array of matching words' implies how to invoke the tool and what it is for. However, it gives no when-to-use versus when-not guidance, no mention of what to do when the part-of-speech is unknown, and no pointer to related tools such as KeywordExtractor or TextLemmatizer.

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