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cliwant

mcp-sam-gov

by cliwant

fdic_industry_summary

Read-only

Retrieve FDIC annual aggregate banking data for the US or a state, including total assets, deposits, net income, and institution counts, split by commercial banks and savings institutions.

Instructions

FDIC industry & state banking-sector ANNUAL AGGREGATES — the FDIC's own roll-ups (keyless FDIC BankFind, api.fdic.gov/banks/summary). The FIRST aggregate/statistical FDIC tool (the other 4 are per-ENTITY, keyed on CERT): total assets, deposits, net income, equity & net interest income + structural counts (institutions, offices, branches, employees) for the whole US banking industry OR one state/territory in one year, split by charter class. Answers 'how big is the US (or a state's) banking industry this year, and how many institutions?' — a question the entity tools cannot express without summing thousands of rows. Exact-key filters (all optional, AND-combined): year (→ YEAR; e.g. 2023 → 121 rows), state (2-or-3-letter → STALP — NOTE the /summary state field is STALP, NOT PSTALP; accepts a jurisdiction code TX/CA/DC/GU/PR… OR a ROLL-UP code USA/US/OT/PI), charterClass (CB = commercial banks, SI = savings institutions; omit for both — there is NO combined row). limit (≤1000, def 100), offset (≤100000), sortBy (allowlisted enum YEAR/ASSET/DEP/NETINC/BANKS, def YEAR), sortOrder (def DESC → newest year / largest first). Returns { summary:[{ year, charterClass, charterClassCode, geography, stateCode, stateFips, scope, isRollup, institutionCount, officeCount, branchCount, employeeCount, totalAssetsUSD, totalDepositsUSD, netIncomeUSD, totalEquityUSD, netInterestIncomeUSD, id }] }. ★ROLL-UP HONESTY: each row crosses charter × geography; STALP ∈ {USA,US,OT,PI} are GEOGRAPHIC AGGREGATES (scope national_total/national_states_dc/territories_total/pacific_islands, isRollup:true), every other STALP is a jurisdiction (isRollup:false) — NEVER sum a roll-up row with jurisdiction rows or across scopes (national_total = national_states_dc + territories_total; a geography's total = its CB row + its SI row), read the national_total (USA) row directly for one national figure; a roll-up is NOT a state. ★NIM is net interest INCOME (a $ sum surfaced as netInterestIncomeUSD), NOT the margin ratio; this endpoint has NO ratio fields (ROA/ROE — derive from netIncomeUSD/totalAssetsUSD/totalEquityUSD). NO name/city filter — FDIC's /summary search param is ignored (returns the whole year); drill to institutions via fdic_search_institutions. HONESTY: totalAvailable is the EXACT meta.total (stable across offset — never the page length); money (ASSET/DEP/NETINC/EQ/NIM) is $thousands → whole USD ×1000 (null-never-0 — a genuine 0 like American Samoa's zero commercial banks stays 0, absent → null), counts (BANKS/OFFICES/BRANCHES/employees) pass through un-scaled (a count ×1000 is a fabrication); a non-int year is rejected pre-fetch (a malformed year is a live HTTP-200 total:0 false-empty); the ONLY honest empty is meta.total:0/data:[] ⇒ complete:true/total:0, every other envelope (400 errors[]/404/non-JSON/missing meta or data) THROWS (never a fake empty); the point-in-time snapshot build time is disclosed. NOTE: FDIC keys on CERT, not SAM UEI/DUNS.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearNoFilter by aggregate YEAR (→ YEAR filter). 1934..current UTC year. e.g. 2023 → the 121 (charter × geography) aggregate rows for 2023. A non-int is rejected pre-fetch (a malformed year is a live HTTP-200 total:0 false-empty).
limitNoRows per page, 1..1000, default 100.
stateNoFilter by geography via the STALP code (uppercase 2-or-3 letters; → STALP filter — the /summary state field is STALP, NOT PSTALP). Accepts a jurisdiction USPS code (TX, CA, DC, GU, PR…) OR a ROLL-UP code: USA (all states+territories), US (states+DC), OT (all territories), PI (Pacific Islands). The output scope/isRollup disambiguates every returned row.
offsetNo0-based row offset for pagination, 0..100000, default 0.
sortByNoSort field (allowlisted enum; default YEAR = aggregate year). An unknown field is rejected before fetch.
sortOrderNoSort direction, default DESC (newest year / largest first).
charterClassNoFilter by charter class (→ CB_SI filter): CB = commercial banks, SI = savings institutions. Omit to return BOTH charter rows for the geography — there is NO pre-combined 'all institutions' row (a geography's total = its CB row + its SI row).
Behavior5/5

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

Annotations already declare readOnlyHint and openWorldHint. The description adds extensive behavioral context: roll-up honesty, that NIM is net interest income (not margin), no ratio fields, money in $thousands, counts unscaled, error handling (non-int year rejected, honest empty), and build-time disclosure. 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is verbose (almost 500 words) and contains many details that could be streamlined. It is well-organized with bullet-like sections and a clear front-loaded summary, but could be more concise for an AI agent. Structure is good but length reduces conciseness.

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 7 parameters, 100% schema coverage, good annotations, and no output schema, the description is exceptionally complete. It explains output structure, edge cases, roll-up behavior, and limitations thoroughly. An AI agent has all necessary context to use the tool correctly.

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

Parameters5/5

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

Schema description coverage is 100%. The description adds meaningful context beyond schema: for year, notes rejection of non-integers; for state, explains STALP vs PSTALP and roll-up codes; for charterClass, clarifies omission returns both rows; for sortBy/sortOrder, defines defaults. Adds value by explaining the meaning of enum values and constraints.

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 provides FDIC industry & state banking-sector annual aggregates, and distinguishes itself from the other four FDIC tools which are per-entity keyed on CERT. It uses specific verbs and resources: 'roll-ups', 'total assets, deposits, net income, equity & net interest income + structural counts'.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool: to answer questions about the size of the US/state banking industry that entity tools cannot express without summing thousands of rows. Also provides alternatives: 'drill to institutions via fdic_search_institutions' and notes what the tool does not do (no name/city filter, no ratio fields).

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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