Skip to main content
Glama

Search OII Reading Room Records

fda_search_oii_records
Read-onlyIdempotent

Search recent FDA Office of Inspections and Investigations reading-room records by company, FEI, record type, country, establishment type, or publish date. This is official FDA document-index metadata with direct links to the posted records, plus incremental extracted document text when available, useful for finding recent 483-style inspection evidence by account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1-500)
stateNoState name
offsetNoResult offset for pagination
countryNoCountry name
date_toNoEnd date for publish_date range (YYYY-MM-DD)
keywordNoKeyword to search in the FDA-provided excerpt and extracted document text
date_fromNoStart date for publish_date range (YYYY-MM-DD)
fei_numberNoFDA Establishment Identifier (FEI number)
record_typeNoRecord type, for example 483
company_nameNoCompany name (fuzzy match)
establishment_typeNoEstablishment type, for example Sterile Drug Manufacturer

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already indicate read-only and idempotent behavior, so the bar is lower. The description adds valuable context by disclosing that results are official FDA document-index metadata with direct links to posted records, and that extracted document text is included incrementally when available. It does not contradict annotations.

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, front-loaded with the core purpose and filters, followed by a concise statement about the content and use case. Every sentence earns its place with no wordiness or repetition of schema details.

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 search tool with 11 parameters and no output schema, the description communicates the essential purpose, filterable attributes, and the value proposition (links + extracted text). It could be more explicit about ordering (e.g., 'recent' implies date ordering) or default behavior, but the description is sufficiently complete for a typical search tool.

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 has 100% coverage, so the baseline is 3. The description briefly lists some filter fields (company, FEI, record type, country, establishment type, publish date) but does not add any meaning beyond what the schema already provides for parameters. It does not compensate with extra detail, so a 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 uses a specific verb ('Search') and clearly identifies the resource ('FDA Office of Inspections and Investigations reading-room records'), listing several searchable fields. It distinguishes itself from sibling tools by naming OII reading-room records and noting the 483-style inspection evidence focus, which sets it apart from general inspection or warning letter searches.

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 clear context for use ('useful for finding recent 483-style inspection evidence by account') and implies a search/filter role. However, it does not explicitly state when not to use this tool or mention alternatives among the many sibling FDA tools, so it lacks explicit exclusions.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes with clear boundaries, such as fda_search_drugs for drug applications and fda_search_510k for device clearances. However, some overlap exists, like fda_device_udi and fda_device_udi_lookup both querying UDI data, which could cause confusion despite differences in scope.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with a clear fda_ prefix, using descriptive verbs like search, get, list, and link. This uniformity makes the set predictable and easy to navigate, with no deviations in naming style.

Tool Count2/5

With 48 tools, the count is excessive for a single server, making it overwhelming and difficult for agents to manage. While the domain is broad (FDA data), the toolset feels bloated with many specialized or overlapping tools that could be consolidated.

Completeness5/5

The toolset provides comprehensive coverage of FDA data domains, including drugs, devices, inspections, compliance, recalls, and facilities. It supports full CRUD-like operations (e.g., search, get, link, save) and lifecycle workflows, with no obvious gaps for the intended purpose.

Resources