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colbyw5
by colbyw5

search_drug_labels

Retrieve drug labeling information from FDA's SPL dataset. Filter by brand name or other fields, paginate results, and count occurrences.

Instructions

Search drug product labeling (SPL) information.

Args: search: openFDA query (e.g. 'openfda.brand_name:"lipitor"'). limit: Max results (1-1000). skip: Offset for pagination. count: Field to count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNo
countNo
limitNo
searchNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It explains parameter behavior (search query format, limit, skip, count) but does not disclose return format, pagination behavior, rate limits, or whether the tool is read-only/destructive. The output schema exists but is not referenced.

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 concise: one sentence for purpose plus a clear bulleted list for parameters. Every sentence adds value, and the structure is front-loaded with the main action.

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

Completeness4/5

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

For a tool with 4 parameters and an output schema, the description covers parameter usage well with examples. It omits response structure and error handling, but output schema exists. Given the sibling tools, some guidance on when to use this tool would improve completeness.

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?

Schema description coverage is 0%, so the description fully compensates. Each parameter is explained with purpose and an example for 'search'. This adds essential meaning beyond the schema's type/default fields.

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 'Search drug product labeling (SPL) information', specifying the verb (search) and resource (drug labeling). It distinguishes from siblings like search_drug_ndc, search_drug_adverse_events, etc., because SPL is a unique domain within FDA data.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus its siblings (e.g., when to search labeling vs NDC or adverse events). The description only explains parameters without context for tool selection.

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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