Retrieve frequently reported adverse reactions for a drug from FAERS with report counts, optionally limited to serious reports.
Most frequently reported adverse reactions for a drug in FAERS (FDA Adverse Event Reporting System), with report counts. Optionally only serious reports.
| Name | Required | Description | Default |
|---|---|---|---|
| drug | Yes | ||
| limit | No | ||
| serious_only | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full disclosure burden. It usefully reveals the data source (FAERS) and that the output is raw report counts rather than causality or disproportionality, but it omits caveats that matter for FAERS data (spontaneous/voluntary reports), behavior on unknown drug names, and whether results are sorted or truncated.
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 front-loaded sentence carries the core purpose, data source, and output content, with the optional filter appended. The trailing fragment is slightly clipped but costs almost nothing in length.
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?
An output schema exists, so return values need not be explained, and the tool has only three simple parameters. What remains missing — FAERS data caveats, the meaning of 'limit', and error behavior for unmatched drugs — is modest given the tool's simplicity and the presence of an output schema.
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 0%, so the description must supply parameter meaning. It covers 'drug' implicitly and 'serious_only' explicitly ('only serious reports'), but says nothing about 'limit' — an agent cannot tell whether it caps the number of reaction terms returned or the number of reports per term, which is a meaningful ambiguity.
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 states a specific resource (most frequently reported adverse reactions), the underlying data source (FAERS), and the return content (report counts), which is far more informative than the tool name alone. It does not explicitly contrast itself with adjacent siblings such as signal_check or drug_recalls, so sibling differentiation is only partial.
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?
There is no statement of when to use this versus signal_check (disproportionality signals) or drug_recalls, both of which an agent could plausibly confuse with adverse-event frequency data. The only usage hint is the trailing 'optionally only serious reports', which describes a parameter rather than a selection rule.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.