FDA enforcement recalls for a specific recalling firm/company — product, reason, classification, status. Source: openFDA (U.S. FDA), public data.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (1-20, default 5) | |
| company | Yes | Recalling firm name (e.g. 'McNeil Consumer Healthcare', 'Baxter') |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for behavioral disclosure. It states the source (openFDA, public data) and the output fields, but does not explain how company matching works (exact vs fuzzy), what happens with no results, or any rate limits or read-only nature. This is a significant gap for a tool with no annotation safety profile.
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 a single sentence with no filler. It front-loads the core purpose and includes the source. The list of output fields is useful but slightly adds length, yet still earns a 4 for efficiency.
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 the tool's simplicity (2 parameters, no output schema), the description is reasonably complete. It covers the purpose, the company parameter, and the return fields. It could benefit from a pointer to sibling health_recalls for broader context, but that is a usage guideline concern, not a completeness gap for this 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 100% coverage for both parameters (company and limit), so the schema already provides the necessary semantics. The description adds minimal extra meaning—only the word 'specific' for company—and does not elaborate on the limit parameter. Baseline 3 is appropriate when the schema handles the parameters.
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 the tool lists FDA enforcement recalls for a specific recalling firm/company, and lists the output focus (product, reason, classification, status). This verb+resource+scope combination distinguishes it from sibling tools like health_recalls, which is a general recall lookup.
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 phrase 'for a specific recalling firm/company' clearly implies when to use this tool (when you have a known company) versus a general recall search. However, it does not explicitly name alternative tools or state when not to use it, so it lacks the explicit exclusion that would push it to a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.