veroq_research_fda

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

No annotations are provided, so the description carries full disclosure responsibility. It details the return format (list of recent FDA actions with drug name, company, action type, date, details) and mentions a cost of 1 credit. This adds value beyond the empty schema, though it could note that the tool is read-only or has no side effects.

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 very concise, using labeled sections (WHEN TO USE, RETURNS, COST, EXAMPLE) for quick scanning. Every sentence serves a purpose, and there is no wasted text. It is well-structured and front-loaded.

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?

Given that there are no parameters and no output schema, the description covers all essential dimensions: purpose, usage, return data, and cost. It lacks information about the time range of 'recent' actions or how many results are returned, but overall it is sufficiently complete for a simple tool.

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 input schema has no parameters, and schema description coverage is 100%. The description does not need to elaborate on parameters, as there are none. A baseline of 4 is appropriate for zero-parameter tools where the schema is fully described.

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 identifies the tool's purpose: tracking FDA drug approvals, rejections, and recalls. The verb 'track' is implied, and the resource is specific (FDA regulatory actions). It distinguishes itself from sibling research tools like veroq_research_bills or veroq_research_regulations by focusing on FDA approvals and recalls.

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 explicitly states when to use the tool: 'To track FDA drug approvals, rejections, and recalls. Important for biotech/pharma stock analysis.' This provides clear context and intended audience. It does not explicitly mention when not to use it, but given the zero-parameter simplicity, that is acceptable.

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