search_units

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

With no annotations, the description carries the full burden. It discloses that omitting queries returns the complete (short) vocabulary, and that unit names are case/locale-sensitive ('g' and 'Gramm' are separate), with invisible consequences for choosing the wrong one. This is key behavioral context beyond the schema.

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?

Two sentences, no filler. The first states the purpose, the second gives a usage recommendation and a concrete warning. Every sentence contributes.

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?

The schema covers parameter descriptions and the output schema exists, so no return format explanation is needed. The description covers the edge case (no queries) and the ambiguity pitfall. For a simple lookup tool, this is fully complete.

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?

The schema already documents both parameters (limit and queries). The description adds meaningful guidance: omitting queries returns the full vocabulary and is recommended when unsure. It reinforces and extends the schema's 'Omit to list everything' with practical advice.

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 opens with 'Look up units of measure, or list them all,' which clearly identifies the resource (units of measure) and the two supported actions (lookup and list). This distinguishes it from sibling tools like create_unit and search_foods.

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?

Explicitly advises to call without queries to list the entire vocabulary when unsure, rather than guessing a name, and warns about Tandoor's 'g' vs 'Gramm' separation. This provides a clear decision rule and alternative, though it doesn't name specific sibling tools.

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