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NCUA credit union data

by io.github.bnovarini
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list_fields

List available fields with plain-language definitions from the data dictionary. Filter by table ('metrics' = computed ratios, 'fact_call_report_curated' = reported amounts, 'dim_credit_union' = attributes), by search text, or both. Fields marked basis=year_to_date reset each January; metric_series can de-cumulate them. Computed metrics available: asset_growth_yoy (Total assets versus the same quarter one year earlier); loan_growth_yoy (Total loans versus the same quarter one year earlier); share_growth_yoy (Total shares and deposits versus one year earlier); member_growth_yoy (Members versus one year earlier); auto_loan_growth_yoy (New plus used vehicle loans versus one year earlier); first_lien_growth_yoy (First-lien 1-4 family loans versus one year earlier); loan_to_share (Loans divided by total shares and deposits); loans_to_assets (Loans divided by total assets); net_worth_to_assets (Net worth divided by total assets (1.0 = 100%)); allowance_to_loans (Allowance for credit losses divided by total loans); net_worth_ratio_ex_cecl (Net worth minus the CECL transition provision, over assets); deposit_mix_share_drafts (Share draft (checking) accounts as a share of total shares and deposits); deposit_mix_regular (Regular shares as a share of total shares and deposits); deposit_mix_money_market (Money market shares as a share of total shares and deposits); deposit_mix_certificates (Share certificates as a share of total shares and deposits); deposit_mix_ira_keogh (IRA and Keogh accounts as a share of total shares and deposits); deposit_mix_non_member (Non-member deposits as a share of total shares and deposits); avg_balance_per_listed_account (Total shares and deposits over the count of share draft, certificate, money market, IRA a…); employees_fte_estimate (Full-time employees plus half of part-time employees); members_per_fte (Members per estimated full-time-equivalent employee); assets_per_fte (Assets per estimated full-time-equivalent employee); compensation_per_fte (Annualized employee compensation and benefits per estimated FTE); operating_expense_per_fte (Annualized non-interest expense per estimated FTE); assets_per_branch (Assets per branch); members_per_branch (Members per branch); compensation_share_of_opex (Employee compensation and benefits as a share of non-interest expense); loans_per_member (Average loan dollars per member); shares_per_member (Average shares and deposits per member); mix_auto (New plus used vehicle loans as a share of total loans); mix_residential_real_estate (First lien, junior lien and other real estate loans as a share of total loans); mix_credit_card (Credit card loans as a share of total loans); mix_commercial (Commercial loans as a share of total loans); delinquency_rate (Loans delinquent two or more months divided by total loans); auto_delinquency_rate (Reportable delinquent vehicle loans divided by vehicle loans); credit_card_delinquency_rate (Delinquent credit card loans divided by credit card loans); net_chargeoff_rate ((Charge-offs minus recoveries), annualized from year to date, over year-end loans); net_chargeoff_rate_avg_loans_4q (Net charge-offs annualized from year to date, over the average of the last four quarter-e…); provision_to_loans (Provision (credit loss expense) annualized over year-end loans); roa_year_end_assets (Return on assets: net income annualized from year to date, over year-end assets); roa_avg_assets_4q (Return on assets: net income annualized from year to date, over the average of the last f…); nim_year_end_assets (Net interest margin: (interest income minus interest expense) annualized from year to dat…); nim_avg_assets_4q (Net interest margin (NIM): same, over the four-quarter average of assets); loan_yield (Yield on loans: interest on loans annualized from year to date, over year-end loans); cost_of_shares (Cost of shares: total interest expense annualized from year to date, over shares and depo…); efficiency_ratio (Non-interest expense divided by (net interest income plus non-interest income)); opex_to_assets (Non-interest expense annualized over assets); fee_share_of_non_interest_income (Fee income divided by non-interest income); net_income_quarter (Net income for the single quarter (year-to-date minus prior quarter)); interest_income_quarter (Interest income for the single quarter); interest_expense_quarter (Interest expense for the single quarter); non_interest_expense_quarter (Non-interest expense for the single quarter); provision_quarter (Provision for loan losses for the single quarter); roa_ncua_ytd (Return on average assets on NCUA's basis: year-to-date net income annualized, over the av…); nim_ncua_ytd (Net interest margin (NIM) on NCUA's basis: (interest income minus interest expense) annua…); loan_yield_ncua_ytd (Yield on loans on NCUA's basis: interest on loans annualized from year to date, over the …); cost_of_funds_ncua_ytd (Cost of funds on NCUA's basis: total interest expense annualized from year to date, over …); net_chargeoff_rate_ncua_ytd (Net charge-off rate on NCUA's basis: (charge-offs minus recoveries) annualized from year …); roa_quarterly (Return on assets for the single quarter: the quarter's net income times 4, over the avera…); nim_quarterly (Net interest margin (NIM) for the single quarter: (interest income minus expense) for the…); loan_yield_quarterly (Yield on loans for the single quarter: the quarter's interest on loans times 4, over the …); cost_of_funds_quarterly (Cost of funds for the single quarter: the quarter's interest expense times 4, over the av…); net_chargeoff_rate_quarterly (Net charge-off rate for the single quarter: the quarter's (charge-offs minus recoveries) …); interest_on_loans_quarter (Interest on loans for the single quarter (year-to-date minus prior quarter)); net_chargeoffs_quarter (Charge-offs minus recoveries for the single quarter)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
tableNo
searchNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It adds real domain context (fields marked basis=year_to_date reset each January; metric_series can de-cumulate them), which is useful. But it says nothing about read-only status, result limits/pagination, or permissions that a metadata tool should disclose, and the bulk of the text is domain content rather than tool behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

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

It is front-loaded well, but the body is an enormous enumeration of roughly seventy computed metrics, many truncated with ellipses, which dwarfs the actionable guidance and makes the definition hard to scan. Much of this belongs in an output schema or reference resource rather than the description.

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?

An output schema exists, so return values need not be explained, and the description supplies the relevant domain context an agent needs to interpret fields and filters. It is largely complete for a discovery tool, missing only pagination/limit behavior and an explicit read-only statement.

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 description coverage is 0%, so the description must carry parameter meaning, and it does for two of three: 'table' receives concrete allowed values with interpretation ('metrics' = computed ratios, 'fact_call_report_curated' = reported amounts, 'dim_credit_union' = attributes) and 'search' is described as search text. The 'limit' parameter is never explained, keeping it short of a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The opening sentence gives a specific verb and resource ('List available fields with plain-language definitions from the data dictionary'), and the table filter values clarify the scope of what can be listed. It partially differentiates from siblings by pointing at metric_series, but does not clearly separate itself from query_metrics or metric_series as the discovery step.

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

Usage Guidelines3/5

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

The description explains how to filter (by table, by search text, or both) and hints at a downstream relationship ('metric_series can de-cumulate them'), which implies usage. However, it never states when an agent should call list_fields versus query_metrics or metric_series directly, so usage is left to inference.

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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