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Glama

Govparse Government Data Gateway

by io.govparse

fda_feed_warningletters

Which firms just received an FDA Warning Letter — an open compliance-gap and remediation clock? Bulk feed over the FDA Warning Letters index, newest-first by issue date: recipient firm, product area (drugs/devices/food/tobacco…), issuing office, alleged-violation subject, and the response / close-out clock. Flat rows, cursor-paginated up to 1000/page, filterable by product_area, subject, close-out state, or since. Observational records — an alleged violation, never an adjudication. [price: $0.05/row]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoRows per page (default 500, cap 1000).
sinceNoOnly letters issued on or after this date (YYYY-MM-DD).
closedNotrue = closed-out letters only; false = open (no close-out) only.
cursorNoOpaque page cursor — pass the previous page's next_cursor unchanged.
officeNoIssuing FDA center / district office fragment (e.g. Center for Drug Evaluation and Research).
subjectNoAlleged-violation subject fragment (e.g. CGMP, Adulterated, Unapproved New Drug).
product_areaNoProduct area(s), CSV: drugs | devices | biologics | food | dietary-supplement | cosmetics | tobacco | veterinary | other.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Without annotations, the description fully carries the burden. It discloses cursor-pagination, filtering, ordering (newest-first), and observational nature. It also includes pricing, which is useful. Minor lacking: no mention of rate limits or auth.

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

Conciseness4/5

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

The description is reasonably concise at three sentences, front-loaded with the core question. Every sentence adds value, though it could be slightly tighter.

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?

Despite no output schema or annotations, the description explains the purpose, output fields, filtering, pagination, constraints, and pricing. It is comprehensive for a feed 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?

Schema coverage is 100%, so baseline is 3. The description adds context by listing returned fields and mentioning filters, but doesn't add significant meaning beyond what the parameter descriptions already provide.

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 it's a bulk feed of FDA Warning Letters, newest-first, with specific fields. It distinguishes from sibling `fda_warningletters_search` by emphasizing it's a feed and observational.

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

Usage Guidelines3/5

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

The description implies usage for bulk listing and filtering, but doesn't explicitly say when to use this feed vs. the search sibling. It mentions 'Bulk feed' but lacks direct guidance on alternatives.

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

All Govparse Government Data Gateway toolsInspect
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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct domain and specific action (e.g., FDA approvals vs clearances vs recalls; firmstanding business360 dossier vs search vs screen). Even overlapping concepts like 'business360' vs 'business360_lookup' are distinguished by input (UUID vs name+state). No two tools appear to do the same thing.

Naming Consistency5/5

All tools use a consistent lowercase snake_case pattern with domain prefix (e.g., fda_*, firmstanding_*, fmcsa_*, govcon_*). Action words (search, lookup, screen, feed, stats) follow predictable usage. The naming is uniform and easy to parse.

Tool Count4/5

38 tools is on the higher end but appropriate for a comprehensive government data gateway spanning multiple agencies and datasets. Each domain has a reasonable number of tools (e.g., FMCSA: 7, OFLC: 6). Could potentially be trimmed slightly, but overall well-scoped for the stated purpose.

Completeness5/5

The tool surface covers the major government data sources comprehensively: FDA (approvals, clearances, recalls), FMCSA (carrier census, safety, insurance, etc.), FSIS, DOJ/OFLC, OSHA/EPA/DOL enforcement, SEC insider filings, clinical trials, VA facilities/opportunities/vendors, and federal contracting. No obvious gaps for the stated gateway purpose.

Resources