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Fdic

by io.github.pipeworx-io

Fdic Failures

fdic_failures
Read-onlyIdempotent

Search FDIC bank failures by date range. Returns bank name, location, CERT ID, failure date, acquiring institution, and fund type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of failure records to return (default 20)
end_dateNoEnd date filter — MM/DD/YYYY ("12/31/2023"), YYYY-MM-DD, or a bare year ("2023")
start_dateNoStart date filter — MM/DD/YYYY ("01/01/2023"), YYYY-MM-DD, or a bare year ("2023")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersYes
failuresYesList of bank failures
total_failuresYesTotal number of bank failures in result set

Schema Changelog

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

  1. Changed2 schema fields changed
    • changedInput schema / properties / end_date / description
      Previous value: -"End date filter in MM/DD/YYYY format (e.g., \"12/31/2023\")"New value: +"End date filter — MM/DD/YYYY (\"12/31/2023\"), YYYY-MM-DD, or a bare year (\"2023\")"
    • changedInput schema / properties / start_date / description
      Previous value: -"Start date filter in MM/DD/YYYY format (e.g., \"01/01/2023\")"New value: +"Start date filter — MM/DD/YYYY (\"01/01/2023\"), YYYY-MM-DD, or a bare year (\"2023\")"
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "failures": {
+      "description": "List of bank failures",
+      "items": {
+        "properties": {
+          "acquiring_institution": {
+            "description": "Institution that acquired the failed bank",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "cert": {
+            "description": "FDIC certificate number",
+            "type": [
+              "string",
+              "number",
+              "null"
+            ]
+          },
+          "city": {
+            "description": "City location",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "failure_date": {
+            "description": "Date of bank failure",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "fund": {
+            "description": "Insurance fund type",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "name": {
+            "description": "Bank name",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "state": {
+            "description": "State code",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "total_assets": {
+            "description": "Total assets at time of failure",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "total_deposits": {
+            "description": "Total deposits at time of failure",
+            "type": [
+              "number",
+              "null"
+            ]
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "filters": {
+      "properties": {
+        "end_date": {
+          "description": "End date filter applied",
+          "type": [
+            "string",
+            "null"
+          ]
+        },
+        "start_date": {
+          "description": "Start date filter applied",
+          "type": [
+            "string",
+            "null"
+          ]
+        }
+      },
+      "type": "object"
+    },
+    "total_failures": {
+      "description": "Total number of bank failures in result set",
+      "type": "number"
+    }
+  },
+  "required": [
+    "total_failures",
+    "filters",
+    "failures"
+  ],
+  "type": "object"
+}
  3. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "limit": 10
+  },
+  {
+    "end_date": "12/31/2023",
+    "limit": 20,
+    "start_date": "01/01/2023"
+  }
+]
  4. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds that it returns specific fields but does not disclose additional behavioral traits beyond what annotations provide, so it meets the baseline without adding extra value.

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?

Description is a single 16-word sentence that is front-loaded with the action verb and efficiently conveys the tool's purpose and output. No unnecessary words.

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 that annotations, full schema coverage, and an output schema exist, the description is sufficiently complete. It covers the core functionality and return fields, though it could mention the default limit or pagination behavior.

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% and already documents all three parameters clearly, including defaults and date formats. The description mentions 'date range' which aligns with start_date and end_date but adds no semantic meaning beyond the schema.

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 searches FDIC bank failures by date range and lists specific fields returned. It effectively distinguishes itself from sibling FDIC tools like fdic_search_institutions or fdic_get_institution.

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 when to use the tool (searching FDIC bank failures by date range) but does not explicitly mention when not to use it or alternatives. However, the purpose is straightforward given the sibling tools.

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

A3.6/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer questions over the same underlying data catalog, and the five polymarket_* tools plus bet_research all analyze prediction-market opportunities. Tools like entity_profile, recent_changes, compare_entities, and resolve_entity also blur together for company research.

Naming Consistency2/5

Names are all snake_case but follow no consistent convention: some are bare verbs (forget, recall, remember, subscribe), some are noun phrases (fdic_failures, entity_profile, pipeworx_trending), and some are verb_noun (fdic_get_institution, generate_llms_txt, validate_claim). Even the fdic_* family mixes noun-only and verb_noun styles.

Tool Count2/5

At 36 tools this exceeds the 25-tool threshold for 'too many.' The count is inflated by redundant meta-tools (three ask_pipeworx variants, discover_tools, suggest_questions, multiple polymarket scanners) and unrelated purpose tools (generate_llms_txt, scan_dependency, ai_visibility_check) that do not belong in an FDIC-named server.

Completeness3/5

The universal ask_pipeworx router gives broad data coverage for almost any factual question, so core lookups are unlikely to dead-end. However, the FDIC-specific surface is thin (only five tools, missing branch/geography/history data), and the server's actual scope is so broad and mixed that no single domain is fully covered end-to-end.

Resources