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jflamb

FDIC BankFind MCP Server

by jflamb

Holding Company Profile

fdic_holding_company_profile
Read-onlyIdempotent

Profile a bank holding company by aggregating financial metrics and listing all FDIC-insured subsidiaries. Look up by holding company name or any subsidiary's CERT number.

Instructions

Profile a bank holding company by grouping its FDIC-insured subsidiaries and aggregating financial metrics. Look up by holding company name or by any subsidiary's CERT number.

Output includes:

  • Consolidated summary with total assets, deposits, and asset-weighted ROA/equity ratio

  • List of all FDIC-insured subsidiaries with individual metrics

  • Structured JSON for programmatic consumption

NOTE: This is an analytical tool based on public financial data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
hc_nameNoHolding company name (e.g., "JPMORGAN CHASE & CO"). Uses NAMEHCR field.
certNoCERT of any subsidiary — looks up its holding company, then profiles the entire HC.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Annotations indicate readOnly and idempotent, so no destructive actions. The description adds valuable context: that it aggregates data across subsidiaries, provides consolidated metrics and a list of subsidiaries, and outputs structured JSON. It also notes it's based on public financial data, reinforcing safe usage.

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 concise, well-structured with bullet points, and front-loads the core purpose. Every sentence adds value without unnecessary detail.

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?

Given the tool's simplicity (2 optional params, full schema coverage, output schema presence), the description provides all necessary information: purpose, lookup options, and output contents. It is complete for agent decision-making.

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?

Input schema coverage is 100% and already describes both parameters (hc_name and cert). The description restates the lookup methods but does not add significant new semantic details 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 profiles a bank holding company by grouping its FDIC-insured subsidiaries and aggregating financial metrics. It specifies lookup methods (by name or subsidiary CERT) and distinguishes itself from sibling tools that focus on individual banks or other analyses.

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 explains what the tool does and how to use it (by HC name or subsidiary CERT), but does not explicitly state when not to use it or direct to alternatives. The unique purpose is clear, but guidance on exclusion could be stronger.

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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