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Search Drugs

search_drugs
Read-onlyIdempotent

Search Structured Product Labels by any combination of name, ANDA/NDA, NDC, RxCUI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ndcNoNDC code (11-digit)
nameNoDrug name (brand or generic)
pageNo1-based page (default 1)
rxcuiNoRxNorm RxCUI
pagesizeNo1-100 (default 25)
manufacturerNoManufacturer name
application_numberNoANDA/NDA number (e.g. "NDA021436")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsNoArray of matching drug labels
pageSizeNoPage size
pageNumberNoCurrent page number
totalPagesNoTotal number of pages
totalResultsNoTotal number of matching results

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds no behavioral details beyond stating the search functionality. It does not contradict annotations, but it provides no additional context about rate limits, result behavior, or side effects.

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 a single sentence, highly concise, and front-loaded with the core purpose. Every word earns its place; there is no extraneous information.

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?

Given the tool's complexity (7 optional parameters, output schema present), the description is adequate. It identifies the key search fields but does not explain pagination or result format. However, the schema and examples cover these details. The description is complete enough for a search tool with good schema coverage.

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?

Schema description coverage is 100%, so each parameter is well-documented in the schema. The tool description does not add meaning beyond the schema; it simply lists the searchable identifiers. The examples in the schema provide some context, but the description itself adds no new semantic value.

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 searches 'Structured Product Labels' using specific identifiers (name, ANDA/NDA, NDC, RxCUI). This is a specific verb+resource combination that distinguishes it from sibling tools like 'get_drug' (which retrieves a single drug) and 'search_within' (which searches within data).

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 implies usage: search by any combination of identifiers. It is clear that this is the primary search tool for drugs, but it does not explicitly state when not to use it or mention alternatives. The context of siblings (e.g., 'get_drug' for a single result) provides implicit guidance.

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

B3.4/5.0
Disambiguation2/5

Multiple tools have overlapping purposes (e.g., ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; deep_research; bet_research and multiple polymarket tools). This makes it difficult for an agent to distinguish which tool to use.

Naming Consistency4/5

Tool names consistently use snake_case and follow a verb_noun or noun_verb pattern. However, some names are very long and descriptive (e.g., polymarket_kalshi_spread, scan_competitor_ai_presence), which is acceptable but slightly inconsistent in length.

Tool Count3/5

With 38 tools, the server is on the high side of reasonable. Many are meta-tools or query routers, which inflates the count. The scope is very broad, covering diverse domains, making the number somewhat justifiable but still feeling heavy.

Completeness3/5

For the Dailymed domain, tools cover label search, retrieval, history, and comparison. However, many other domains (e.g., finance, prediction markets) rely on a handful of routing tools (ask_pipeworx) rather than dedicated tools, leaving the coverage uneven and not fully self-contained.