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lzinga

US Government Open Data MCP

fdic_failures

Read-only

Retrieve FDIC-insured bank failures since 1934, including failure date, estimated cost, resolution type, and acquiring institution. Filter by state or year range for targeted results.

Instructions

Get FDIC-insured bank failures — all failures since 1934. Includes failure date, estimated cost to FDIC, resolution type, and acquiring institution. Filter by state: PSTALP:"GA", by year range, or combine filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNoLucene-style filter: 'PSTALP:"GA"', 'FAILDATE:[2008-01-01 TO 2010-12-31]'
sort_byNoSort field: 'FAILDATE' (default), 'COST', 'QBFASSET'
sort_orderNoSort direction
limitNoMax results (default 25, max 100)
offsetNoPagination offset
Behavior4/5

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

Annotations already declare readOnlyHint=true, and description confirms read-only nature. It adds scope ('all failures since 1934') but doesn't detail pagination limits (though schema handles that). No contradictions.

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?

Three sentences: first states purpose and scope, second lists returned fields, third gives filtering guidance. Front-loaded, no redundant words across multiple sentences.

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, description mentions key return fields. Parameters well-documented in schema with examples. For a simple filtered-list tool with good annotations, it's complete.

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 baseline is 3. Description adds value by providing a specific filter example ('PSTALP:"GA"') and explaining that filter combines with year range, going beyond schema's generic 'Lucene-style filter'.

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?

Description clearly states the tool returns FDIC-insured bank failures since 1934, listing specific data fields (failure date, cost, resolution type, acquiring institution). It distinguishes from sibling FDIC tools like fdic_deposits or fdic_summary by focusing on failures.

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?

Description provides concrete filtering examples (by state with 'PSTALP:"GA"', by year range, or combine filters). While it doesn't explicitly compare to siblings or state when not to use, these examples give clear usage context.

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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