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Fdic

by io.github.pipeworx-io

Fdic Financials

fdic_financials
Read-onlyIdempotent

Get quarterly financial metrics for a bank by CERT ID. Returns assets, deposits, net income, interest income, loan losses, ROA, ROE, efficiency ratio.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
certYesFDIC certificate number
limitNoNumber of quarterly reports to return (default 8, which is 2 years)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
certYesFDIC certificate number
financialsYesList of quarterly financial reports
total_reportsYesTotal number of financial reports

Schema Changelog

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

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "cert": {
+      "description": "FDIC certificate number",
+      "type": "string"
+    },
+    "financials": {
+      "description": "List of quarterly financial reports",
+      "items": {
+        "properties": {
+          "efficiency_ratio": {
+            "description": "Efficiency ratio",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "interest_income": {
+            "description": "Interest income in dollars",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "loan_losses": {
+            "description": "Loan losses in dollars",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "net_income": {
+            "description": "Net income in dollars",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "net_interest_margin": {
+            "description": "Net interest margin ratio",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "report_date": {
+            "description": "Report date",
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "roa": {
+            "description": "Return on assets ratio",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "roe": {
+            "description": "Return on equity ratio",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "total_assets": {
+            "description": "Total assets in dollars",
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "total_deposits": {
+            "description": "Total deposits in dollars",
+            "type": [
+              "number",
+              "null"
+            ]
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "total_reports": {
+      "description": "Total number of financial reports",
+      "type": "number"
+    }
+  },
+  "required": [
+    "cert",
+    "total_reports",
+    "financials"
+  ],
+  "type": "object"
+}
  2. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "cert": "628"
+  },
+  {
+    "cert": "628",
+    "limit": 12
+  }
+]
  3. First observed

TDQS

A3.6/5.0
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 extra behavioral context beyond listing return fields, which is partially redundant with the output schema. No contradiction with 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 a single concise sentence, front-loaded with the core action. Every word serves a purpose, with no unnecessary detail.

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 simplicity and the presence of an output schema, the description covers the essential information. However, it could mention the default value for 'limit' (8) for added completeness.

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% for both parameters (cert and limit), so the schema alone adequately documents them. The description mentions cert but adds minimal extra 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 the tool's function: 'Get quarterly financial metrics for a bank by CERT ID.' It specifies a specific verb and resource, lists key return metrics, and distinguishes itself from sibling tools like fdic_failures and fdic_search_institutions.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention scenarios, prerequisites, or comparisons to other FDIC tools, leaving the agent to infer applicability.

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