Word frequency

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description adds real behavioral detail beyond them: case is ignored, words under 3 letters are dropped unless include_common_words is set, and each result carries a count and a share-of-text. It does not mention tokenization limits or handling of punctuation, but the added context is substantive.

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?

Front-loaded with the purpose, then a compact parameter rundown and filtering rules. The trailing example is useful but ends with a stray punctuation artifact ("essay?."), a small blemish on an otherwise tight description.

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?

An output schema exists, so the return format need not be spelled out, and the description still notes that each word comes with a count and a share. Combined with the disclosed filtering rules, an agent has enough to call this correctly; only edge cases like punctuation handling are absent.

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 75%, and the description goes further than the schema by spelling out what include_common_words actually means (the, and, of, to) and how it interacts with the short-word filtering rule. top and min_count are only restated with their defaults, which the schema already supplies.

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+resource (word frequency) and the intent (spot overused or repeated terms), which is genuinely distinguishable from count_text or readability_scores. It never names a sibling tool or draws an explicit boundary, so it stops short of 5.

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?

Gives a clear usage context ("spot overused or repeated terms") and an example query ("Which words do I overuse in this essay?"), so an agent knows when this applies. It offers no when-not guidance and does not point to alternatives such as count_text.

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