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

Annotations already declare read-only, idempotent, closed-world behavior, so the bar is lower. The description still adds real context: the provenance of candidates (kontekst's similar-word lists), the warning that results may be related or opposite words, and the ambiguity handling via `other_readings`.

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?

Purpose and the replacement-ready guarantee are front-loaded, followed by the candidate-source caveat and ambiguity note. Dense with no filler, though the parenthetical example and reading guidance make it a fairly long block for a six-parameter tool.

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?

Output schema exists, so return values need not be re-explained, yet the description proactively explains the `other_readings` output field's purpose and how to use it. Combined with the synonymy caveat and inflection guarantee, an agent has everything needed to call and interpret this tool.

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 83% (goal, lang, safe, word, sentence all documented), so baseline would be 3. The description adds semantic value beyond the schema by stressing that `word` must be the surface/inflected form as it stands in the text and explaining why infllected output matters for substitution.

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 (returns alternatives for a word) plus the key differentiator: candidates are pre-inflected to match the input's case/number/gender/person so they can be dropped into the sentence. The example (`konzistentnoj` -> `dosljednoj`) and the caveat that candidates may be related or opposite rather than synonyms cleanly separate it from lookup_word, get_forms, and find_expression.

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 concrete in-task guidance: choose by meaning rather than assuming synonymy, and when the input form is ambiguous use `other_readings` to pick the form the sentence needs. It does not explicitly name when to prefer a sibling tool (e.g. lookup_word for definitions), but the replacement-in-context scenario is clear.

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