get_fda_activity

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

No annotations provided, so description carries full burden. It discloses auto-fallback behavior and decoding of status codes. Lacks disclosure of rate limits or error handling, but adds significant context beyond 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?

Three sentences with no wasted words. Purpose is front-loaded, and each sentence adds value.

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?

Input semantics are well-covered, but no output schema or description of return fields is provided. For a tool with no output schema, the description should mention what data fields are returned.

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%, baseline 3. Description adds meaning: clarifies kind values, explains query accepts brand/generic names, and explains sponsorFallback parameter.

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 it gets FDA submission and approval activity for a drug or sponsor, mentioning specific filing types (NDA/BLA, approvals, supplements). This is distinct from sibling tools like get_insider_transactions or get_sec_filings.

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?

Explains when to use kind='drug' vs kind='sponsor' and describes auto-fallback behavior. However, it does not explicitly distinguish from alternatives like search_clinical_trials for drug-related queries.

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