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Openfda Describe Fields

openfda_describe_fields
Read-only

Return the searchable field paths for an openFDA endpoint, grouped by category with type and description. Use before constructing a search query to find the correct dotted field path — field names differ per endpoint and are not discoverable from the tool schema alone.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endpointYesopenFDA endpoint to describe (e.g. "drug/event", "drug/shortages", "device/510k"). Must be one of the cataloged endpoints.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
groupsNoField groups for this endpoint
endpointNoThe endpoint these fields apply to
queryTipsNoopenFDA query syntax reminders relevant to this endpoint

TDQS

A4.1/5.0
Behavior3/5

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

The readOnlyHint annotation already signals this is a safe read operation. The description adds behavioral context beyond that: it returns grouped categories with type and description, and emphasizes that field paths differ across endpoints. This is useful but does not describe the exact output structure; however, an output schema exists, so the return format is already documented. The description supplements annotations adequately.

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 two sentences with no filler. The core purpose is front-loaded, followed immediately by the usage context and the rationale for why this tool exists. Every sentence earns its place, and the structure makes it easy for an agent to quickly grasp the tool's role.

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?

For a simple one-parameter discovery tool with an output schema already present, the description is fully complete. It explains what the tool does, when to use it, and why it's necessary, leaving no missing information that an agent would need to make a correct call. The presence of the output schema covers return values, so no further explanation is required.

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

Parameters3/5

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

The input schema provides 100% coverage for the single 'endpoint' parameter, including an enum of valid values and a description. The tool description adds a rationale for why the endpoint parameter is needed (to identify the correct field paths), but does not provide additional syntax or format details beyond the schema. Given full schema coverage, the baseline score of 3 is appropriate.

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 clearly states the tool's purpose: 'Return the searchable field paths for an openFDA endpoint, grouped by category with type and description.' It identifies a specific verb (return), resource (field paths), and the grouping/type/description outcome. This distinguishes it from sibling search/count tools, which operate on data rather than metadata.

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?

The description provides explicit when-to-use guidance: 'Use before constructing a search query to find the correct dotted field path.' It also explains why (field paths differ per endpoint and are not discoverable from the schema). It does not explicitly name an alternative tool, but the context of 'before constructing a search query' implies the correct timing and alternative search tools. This is clear usage guidance but lacks an explicit exclusion statement.

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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TDQS

A4/5.0
Disambiguation5/5

Each tool targets a distinct FDA endpoint or analytic function. Search tools are separated by domain (adverse events, animal events, recalls, tobacco, etc.), and utility tools (count_values, describe_fields, dataframe_describe/query, drug_profile) serve unique purposes without overlap. An agent can clearly identify which tool to call for a given task.

Naming Consistency5/5

All tools follow a consistent openfda_<action>_<object> pattern in snake_case. Search tools use search_<domain>, while utility tools use clear verbs like get, lookup, count, describe, and query. The only slight deviation is drug_profile (a noun phrase), but it remains intuitive and fits the naming style.

Tool Count5/5

With 14 tools, the server is well-scoped for its purpose of providing access to multiple openFDA endpoints. Each tool covers a distinct resource or analytic capability, and none feel redundant. The count sits comfortably within the ideal range for a domain-specific server.

Completeness5/5

The server covers the major openFDA data categories: adverse events (human/animal), device clearances, drug approvals, shortages, recalls, tobacco, labels, and NDC lookup. It also provides robust analytics via count_values and dataframe queries, plus field discovery. There are no obvious gaps for the stated domain, and the composite drug_profile fills integration needs.