render

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

No annotations are provided, so the description carries full burden. It discloses that renderings come from multiple sources, handles polysemy by returning per-sense results, and includes the full output schema. No behavioral contradictions.

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 well-structured with a clear purpose, usage context, source attribution, and output format. Every section adds value without redundancy.

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?

Given the presence of an output schema (described in detail), the description covers all necessary context: input parameters, output structure, data sources, and when to use. Nothing is missing for effective tool selection and invocation.

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% (no parameter descriptions in schema), but the description includes an 'Args' section explaining 'en' (English word) and 'sense' (optional filter). This adds full meaning beyond the schema property titles.

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 clearly states the tool's purpose: 'Get authentic Ukrainian renderings for an English word or sense.' It uses a specific verb ('Get') and resource ('Ukrainian renderings'), and the context of translation/vocabulary tasks distinguishes it from sibling tools like search or substantiate.

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 provides explicit when-to-use guidance: 'Use this for translation or vocabulary tasks where you want idiomatic Ukrainian (not a calque or AI-guessed translation).' It does not explicitly list when not to use or compare to siblings, but the context is clear.

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