Sansglu

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuinely new behavioral context: it discloses what is returned (Sansglu's label plus the place's own website as source) and the failure mode (no record found), which matters given there is no output schema. It does not mention rate limits or ambiguity handling.

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 sentences, all load-bearing: trigger cases first, return behavior second, exclusions last. No restatement of the title or filler.

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 single-parameter, read-only lookup with no output schema, the description covers triggers, return shape, and scope boundaries. Nothing needed to call it correctly is missing.

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 100% and the single parameter already documents length bounds and the 'never a street address or coordinates' constraint. The description adds little beyond the schema, though its example queries reinforce the natural-language phrasing. Baseline 3 is appropriate when the schema does the heavy lifting.

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 and resource (check gluten-free status of one named place) and immediately differentiates from the sibling by excluding place discovery. An agent can distinguish it from find_gluten_free_places without opening either schema.

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 triggering phrasings ('is Nami Nori gluten free?') and explicit exclusions: not for finding new places, and never for packaged foods, grocery products, brands or ingredients. The only alternative tool in the sibling set is ruled out by the 'do not use to find new places' clause.

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

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so safety is covered. The description adds real value beyond that by disclosing the return shape (places on a map, each with its gluten-free label and its own website as source) and the data provenance (Sansglu's database).

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 trigger condition, then returns, then exclusions — a sensible order with no wasted preamble. The long run of near-duplicate example queries is slightly redundant, though each illustrates a distinct phrasing pattern the agent should accept.

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?

No output schema exists, and the description compensates by explaining what comes back and where it comes from. Combined with complete schema coverage and annotations covering the safety profile, an agent has everything needed to call this correctly and to avoid the out-of-scope questions.

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 description coverage is 100%, so all three parameters are already documented, including the enum for label_filter and the limit guidance. The description's example queries reinforce the expected 'in their words' phrasing for query but add no syntax or constraint beyond what the schema provides; baseline 3 applies.

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 (find) and resource (gluten-free places) with clear scope: it searches Sansglu's gluten-free database and returns map results. However, it never distinguishes itself from the sibling check_place_gluten_free_status, so an agent must infer that one searches for places while the other checks a known place.

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 explicit positive triggers (someone asking where to eat gluten-free, in a named place or near them) backed by concrete utterance examples, plus an explicit negative list: recipes, packaged foods, grocery brands, ingredients, booking tables, hotels, symptoms or medical questions. The only omission is naming the sibling as the alternative for status lookups.

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