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Limecooler

fda-mcp

by Limecooler

list_searchable_fields

Discover searchable field names, types, and descriptions for any OpenFDA endpoint before constructing queries.

Instructions

List searchable fields for any OpenFDA endpoint. Returns field names, types, and descriptions.

When to use: Call this BEFORE searching if you're unsure which field names to use in a search query. Field names vary between endpoints.

Args: endpoint: One of the 21 OpenFDA endpoint paths: Drug: drug/event, drug/label, drug/ndc, drug/drugsfda, drug/enforcement, drug/shortage Device: device/event, device/510k, device/pma, device/classification, device/enforcement, device/recall, device/registrationlisting, device/udi, device/covid19serology Food: food/event, food/enforcement Other: other/historicaldocument, other/substance, other/unii, other/nsde category: "common" for the most frequently used fields (default), "all" for the complete field listing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
categoryNocommon
endpointYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden. It transparently states the output ('field names, types, and descriptions') and the scope (all 21 endpoints, common vs. all fields). Although it doesn't explicitly say 'read-only', 'List' and 'Returns' make the non-mutating behavior clear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but every part earns its place: a one-sentence summary, a usage pointer, and a well-structured Args block. The endpoint list is necessary because the schema offers no descriptions. It is front-loaded and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity, the presence of an output schema, and the lack of annotations, the description is complete. It fully covers the endpoint and category parameters, explains when to use the tool, and states what results to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description must compensate. It does: the 'Args' section enumerates every allowed endpoint path grouped by Drug/Device/Food/Other, and explains the category parameter ('common' default, 'all' complete listing). This is far more informative than the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'List searchable fields for any OpenFDA endpoint. Returns field names, types, and descriptions.' This clearly distinguishes it from siblings like search_fda (which executes searches) and count_records (which counts records).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit when-to-use guidance: 'Call this BEFORE searching if you're unsure which field names to use in a search query. Field names vary between endpoints.' While it does not name a specific alternative tool, the 'before searching' naturally points to the search_fda sibling.

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

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