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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds behavioral context beyond annotations: it uses PostgreSQL text search, supports multi-word relevance ranking, and can be filtered by classification, product_type, or date range. It does not describe the return format or pagination details, but given the strong annotation coverage, this is sufficient.

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 concise, front-loaded with the main purpose, and includes a helpful examples clause and related tools in a compact format. Every sentence earns its place; no redundancy or fluff.

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 tool with 8 parameters and no output schema, the description covers the search behavior, ranking, filters, and related tools. It doesn't explicitly state the return structure, but the absence of an output schema makes that less critical. The description is sufficiently complete for an agent to understand the tool's role and typical use.

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?

Input schema coverage is 100% with descriptive parameter properties, so baseline is 3. The description adds some context by mentioning filters (classification, product_type, date range) and giving example queries, but these largely mirror the schema. No additional parameter meaning is provided beyond what the schema already documents.

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 performs full-text search across recall reasons and product descriptions, using PostgreSQL text search. It specifies the resource (FDA recall data) and the verb (search/find), and distinguishes itself from related tools by naming fda_search_enforcement (search by company name, classification, status) and fda_recall_facility_trace (trace to manufacturing facility).

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 related tools with their distinctive search capabilities, helping an agent choose between this and alternatives. It implies this tool is for semantic/text-based searches over recall text, while naming other tools for company-name or facility-trace use cases. It lacks a direct 'use when...' phrasing but is nevertheless clear.

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