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

Annotations already declare readOnly, idempotent, non-destructive, and openWorld, so the safety profile is covered. The description adds the provenance (Drugs@FDA) and the novel-drug/NME flag, which is useful, but says nothing about defaults, page sizes, or result caps.

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?

A single dense passage that front-loads what it returns and then lists fields and filters without filler. The field enumeration is long but each item is meaningful.

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?

With a full output schema and rich annotations, the return shape and safety profile are already covered, so the description only needs to frame scope — which it does. Minor gap: no stated default for the days window or result limit.

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%, so the schema already documents all four parameters. The description restates the sponsor, days, and original-vs-supplemental filters but adds no syntax or format detail beyond the schema, and omits limit entirely. 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?

States a specific verb (list) and resource (FDA drug approvals), plus the exact source (Drugs@FDA) and content types (new drugs, generics, biologics). This clearly separates it from neighbors like list_fda_recalls, get_drug_label, and get_drug_safety.

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?

It frames the use case ('which companies just won FDA approval') and names the filter dimensions, implying usage, but never says when to prefer this over sibling tools like list_fda_recalls or get_drug_safety, and offers no exclusions.

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