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JerBouma

Finance Toolkit

by JerBouma

jobs

Read-onlyIdempotent

Retrieve labour and social metrics by country, including unemployment, productivity, population, poverty, and income inequality. US nonfarm payrolls and initial jobless claims are also covered.

Instructions

Labour and social metrics by country (unemployment rate, labour productivity, population statistics, poverty rate, income inequality). Requires countries='United States' — use comma-separated values for multiple countries. Do NOT use tickers= for this tool. Supports start_date/end_date and quarterly=true. Supports rolling=N (moving-average smoothing) and trailing=N (trailing N-period sum) on the raw series. Also includes two US-only, FRED-backed labor indicators (get_nonfarm_payrolls, get_initial_jobless_claims) — these require a FRED API key and only return a 'United States' column regardless of the countries= argument.

Available indicators: get_income_inequality, get_labour_productivity, get_population_statistics, get_poverty_rate, get_unemployment_rate, get_nonfarm_payrolls, get_initial_jobless_claims.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lagNoNumber of periods to lag when computing growth rates.
growthNoReturn period-over-period growth rates instead of absolute values.
periodNoObservation frequency, e.g. 'monthly', 'quarterly', or 'annual'.
rollingNoRolling window size in number of periods. When set, the metric is computed over a smoothly overlapping trailing window across the full history (e.g. period='monthly' and rolling=6 gives a rolling 6-month value) instead of one value per period, or (for economics indicators) a simple moving average used to smooth the raw series.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-08-19
trailingNoTrailing window size in number of periods. Sums the raw values over the trailing N periods (e.g. trailing=4 on quarterly data gives a trailing-4-quarter / TTM-style sum) instead of returning one value per period.
countriesNoComma-separated country names, e.g. 'United States,Germany,Japan'.
indicatorYesName of the specific metric to calculate, e.g. 'get_asset_turnover_ratio'. Required — omitting it returns the list of available indicators.
quarterlyNoReturn quarterly data instead of annual when True.
start_dateNoStart of the date range in YYYY-MM-DD format.2021-08-20
gmdb_sourceNoUse the Global Macro Database as the data source when True, rather than the OECD. The two are independent providers with different country and period coverage; both return rates and ratios as decimal fractions.
standardizeNoReturn the Z-Score (standard score) instead of the raw values, i.e. how many standard deviations each value is from the mean of its own series. When combined with growth=True, the growth values are standardized instead of the raw values.
show_columnsNoComma-separated names to filter the output. For historical data use the key names visible in any response record (e.g. 'Close,Volume,Return'). For financial statements use the 'metric' field values from the response (e.g. 'Revenue,Net Income,EBITDA'). Call the tool once without this parameter to see all available names, then repeat with show_columns to reduce response size and token usage.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Beyond the readOnly/openWorld/idempotent annotations, the description discloses meaningful behavioral traits: two indicators are US-only and ignore the countries argument, they require a FRED API key, and they always return only a 'United States' column. It also clarifies that rolling is moving-average smoothing and trailing is a trailing-period sum, adding real value beyond the annotations.

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

Conciseness4/5

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

The description is dense but well organized: scope, key usage constraints, transformation options, special-case caveats, and a clear indicator list. The indicator list partially duplicates the schema enum, and the 'Requires countries="United States"' phrasing is slightly ambiguous, but every sentence contributes operational content and the text is front-loaded with the core purpose.

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 13 parameters, an output schema, and a multi-indicator tool, the description covers the critical operational context: country requirements, date/quarterly support, rolling/trailing transforms, FRED-specific limitations, and the full indicator set. An output schema exists and covers return structure. Minor gaps include not clarifying the OECD/GMDB source distinction in the description and the slightly ambiguous 'Requires countries' wording.

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?

The schema already documents all 13 parameters with good descriptions, so the baseline is 3. The description adds extra semantic value by explaining comma-separated countries, prohibiting tickers, clarifying rolling/trailing behavior on raw series, and highlighting country/API-key constraints for FRED indicators. It does not exhaustively elaborate every parameter, but the schema covers those adequately.

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 scope: 'Labour and social metrics by country' and enumerates the exact indicators available (unemployment, productivity, population, poverty, income inequality, nonfarm payrolls, initial jobless claims). This distinguishes it from sibling tools like 'macroeconomics' or 'government' and gives a specific, actionable purpose.

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 gives strong practical guidance: countries must be specified, comma-separated values are supported, tickers should NOT be used, and date/quarterly/rolling/trailing parameters are supported. It also flags the FRED API key requirement and US-only behavior for two indicators. However, it does not explicitly name alternative tools or state when to prefer a sibling tool over this one.

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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