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

Annotations already mark the tool as read-only, idempotent, and open-world. The description adds a valuable behavioral nuance: the SFDA leaves approval_date blank on the newest rows, and an empty date means the date hasn't been published yet rather than a missing record. This is non-obvious behavior that an agent needs to interpret results correctly, going beyond what annotations provide.

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 two sentences, front-loaded with the core purpose, and efficiently packs the data fields and a critical caveat about date blanks. No wasted words; every sentence earns its place.

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 simple list tool with no output schema, the description covers the essential output fields and includes the notable date behavior. It could mention pagination specifics, but the schema already handles page semantics. The description is complete enough for an agent to invoke the tool correctly and interpret results.

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 descriptions already fully document all three parameters (page, trade_name, scientific_name) with usage details like zero-indexing, default values, and substring filtering. The description adds no additional parameter semantics beyond listing the return fields, so it meets the baseline for 100% schema coverage.

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 returns recent SFDA drug approvals in Saudi Arabia, explicitly listing the data fields (request type, drug type, trade name, scientific name, strength, dosage form, approval date). This is a specific verb-resource combination that distinguishes it from sibling tools like sfda_clinical_trials or sfda_drug_search, which cover other aspects of drug data.

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 context that this is for approvals and lists them newest first, but it does not explicitly state when to prefer this over alternatives like sfda_drug_search or sfda_drug_details. The usage is implied by the resource type, but there is no mention of exclusions or alternative tool selection criteria.

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