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

With no annotations, the description carries the full behavioral burden. It usefully discloses one non-obvious behavior (inflected forms like 'આંખોમાં' are matched to their base word) and the script constraint, but says nothing about not-found handling, result size, or whether the lookup is a live or cached/single-source dictionary.

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, front-loaded with the purpose, then usage, then input format. No filler, though the script and inflection notes could be consolidated into one input-format sentence.

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 one-parameter read-only lookup with no annotations and no output schema, the description covers purpose, triggers, input format, and one normalization behavior, and it enumerates the kinds of information returned (meaning, part of speech, usage). Only not-found behavior and result shape remain unstated, which is a minor gap.

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 0%, so the description must compensate, and it does: it specifies the required script (Gujarati, e.g. 'પાણી'), forbids romanized input, and notes that inflected forms are normalized. That is meaningful guidance well beyond a bare "Word" string field.

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?

"Look up the meaning of a Gujarati word in the dictionary" gives a specific verb (look up) and resource (dictionary entry) with a clear language qualifier. It does not explicitly name the siblings (synonyms, idioms) or state what it is not, so an agent must infer the boundary from the word "meaning" alone.

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 names concrete triggering conditions: the user asks what a word means, its part of speech, or how it is used in a sentence. It gives no explicit exclusion against the synonyms/idioms siblings, but the positive triggers are specific enough to route most requests.

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