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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and web-sourced behavior are covered. The description adds the useful fact that results mix product, collection, and query matches, but nothing about ordering, limits behavior, or response shape (which the output schema carries). Adequate but not rich.

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 tight sentences: the core purpose first, then the disambiguation routing. No filler, no repetition of schema details.

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 read-only suggest endpoint with full schema coverage, output schema, and read-only/open-world annotations, this gives an agent everything needed to call it and to pick the right sibling. Only marginal gaps remain (no note on when a partial query is appropriate).

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% – q, limit (default 10, max 20) and types (product, collection, query) are all documented in the schema itself. The description's mention of the three match types loosely mirrors the types parameter but adds no format or syntax detail beyond the schema. 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?

Specific verb ('Fetch predictive-search suggestions') plus resource (Allbirds search) and it enumerates the three match types returned (product, collection, query). It also names the sibling tools it is not, so an agent can distinguish it from allbirds_products/collections/sitemaps without opening a 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?

Explicitly routes the agent to allbirds_products (browse product records), allbirds_collections, and allbirds_sitemaps for their respective jobs, which is clear alternative guidance. It stops short of stating the positive when-to-use condition for this tool (autocomplete/typeahead for a partial query) or any exclusion.

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