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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), so the bar is lower, and the description still adds real context: the counts are spontaneous reports, not incidence — a genuine interpretive caveat that prevents misuse. It also discloses the auth/billing model (free daily allowance, then $0.05 USDC via x402 or 3 credits with X-API-KEY), which matters for invocation planning. It stops short of noting recency or reporting-bias limits.

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?

Two sentences, front-loaded with the data source and return shape, then the caveat, then the billing parenthetical. The pricing clause is boilerplate but genuinely actionable, so little is wasted; the payload is dense and well ordered.

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 no output schema, the description carries the return-shape burden and does so: total counts, serious counts, and top MedDRA reactions with counts. Since only one fully-documented parameter exists and safety annotations are present, remaining gaps are minor — how many 'top' reactions are returned and whether a time window applies are unstated.

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 description coverage is 100% for the single 'slug' parameter, so the schema already carries the semantics. The description adds nothing about the slug (format, where to obtain it), leaving it at the baseline for a fully-documented single 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?

States a specific verb-resource pair and data source: 'FDA FAERS adverse-event signal' returning total and serious report counts plus top MedDRA reactions. It is clear what an agent gets back, but it never separates itself from the sibling get_safety, which is a plausible alternative for the same underlying need.

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?

Usage is only implied by the data source ('FDA FAERS adverse-event signal') — an agent infers this is the safety-signal lookup rather than a trial or regulatory lookup. There is no explicit when-to-use, no exclusion, and no mention of when get_safety or get_approvals would be the better pick.

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