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by io.github.pipeworx-io
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Fda Warning Letters

fda_warning_letters
Read-onlyIdempotent

Search FDA WARNING LETTERS — official enforcement letters FDA sends firms for violations (CGMP, adulterated/misbranded products, unapproved claims). Answers "has received an FDA warning letter", "recent FDA warning letters about supplements/devices". By default search matches the RECIPIENT company the letter was issued to, so the answer is about that firm's own enforcement history; set match:"fulltext" to search the whole letter record instead, which also finds letters that merely mention a firm. Every row reports matched_field so a caller can tell "issued to" from "mentions". Covers the 3,680 letters fda.gov publishes from 2021 onward — recipient company, posted and issued dates, issuing FDA office, subject and a link to the full letter text — and, for a firm with nothing in that window, falls back to the FDA compliance-actions archive of older letters back to 2010, which gives the firm, place, product type and issue date but no document. Every row says which of the two it came from. Live, no caller credential needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax letters to return, 1–50 (default 10). Newest first.
matchNoHow `search` is applied. "recipient" (default) keeps only letters whose addressed company matches. "fulltext" returns every record matching anywhere in its indexed text, including letters that only mention the term.
searchNoCompany the letter was issued to (e.g. "Elanco", "Merck Sharp & Dohme") under the default match mode. Under match:"fulltext" this is a free-text query over the whole record — a product ("supplement") or violation topic ("CGMP"). Omit for the most recent letters.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "search": "Blooming"
-  },
-  {
-    "limit": 20,
-    "search": "supplement"
-  }
-]New value: +[
+  {
+    "search": "Elanco"
+  },
+  {
+    "limit": 20,
+    "match": "fulltext",
+    "search": "supplement"
+  }
+]
    • addedInput schema / properties / match
      Added value: +{
+  "description": "How `search` is applied. \"recipient\" (default) keeps only letters whose addressed company matches. \"fulltext\" returns every record matching anywhere in its indexed text, including letters that only mention the term.",
+  "enum": [
+    "recipient",
+    "fulltext"
+  ],
+  "type": "string"
+}
    • changedInput schema / properties / search / description
      Previous value: -"Full-text search — a company name (e.g. \"Blooming\"), product (\"supplement\"), or violation topic (\"CGMP\"). Omit for the most recent letters."New value: +"Company the letter was issued to (e.g. \"Elanco\", \"Merck Sharp & Dohme\") under the default match mode. Under match:\"fulltext\" this is a free-text query over the whole record — a product (\"supplement\") or violation topic (\"CGMP\"). Omit for the most recent letters."
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "search": "Blooming"
+  },
+  {
+    "limit": 20,
+    "search": "supplement"
+  }
+]
  3. Added

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses data coverage (3,680 letters from 2021 onward), the older-archive fallback to 2010, that older records lack a document link, that every row reports its source, and that no caller credential is needed. This is substantial behavioral context that annotations alone do not provide.

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 dense and front-loaded with the core purpose, and every sentence adds useful operational detail. It is somewhat long for a three-parameter tool, but the added coverage and fallback details are not filler.

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?

Although there is no output schema, the description enumerates the fields returned for both data sources, explains the fallback behavior, notes credential requirements, and clarifies match semantics. An agent has enough information to invoke the tool correctly and interpret its results.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning by explaining how 'search' behaves under the default recipient mode versus fulltext mode, and that matched_field lets callers distinguish 'issued to' from 'mentions'. This goes beyond the schema's field descriptions.

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 opens with 'Search FDA WARNING LETTERS', naming a specific verb and resource, and then clarifies the scope with official enforcement letters for violations such as CGMP and unapproved claims. It gives concrete example questions that an agent would use to invoke it, making the purpose immediately actionable.

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 gives clear guidance on when to use the default 'recipient' match versus match:'fulltext', and explains the fallback to older letters when no recent records exist. It does not explicitly compare against sibling tools like fda_complete_response_letters, so it stops short of full alternatives 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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