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JerBouma

Finance Toolkit

by JerBouma

jobs

Read-onlyIdempotent

Retrieve labour and social metrics such as unemployment rate, labour productivity, population statistics, poverty rate, and income inequality for specified countries.

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.

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

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.2026-07-14
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.2021-07-15
gmdb_sourceNoUse the OECD Global Macro Data Bank as the data source when True.
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?

Annotations indicate readOnlyHint, openWorldHint, and idempotentHint, which the description does not contradict. The description adds context beyond annotations by listing indicators, specifying parameter constraints, and warning about incorrect parameter 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, beginning with the tool's purpose, moving to usage guidelines, and ending with a list of indicators. Every sentence provides necessary information without redundancy.

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 13 parameters (1 required) and an output schema, the description covers key usage patterns, explains multiple parameter interactions, and lists all possible indicator values. It provides sufficient context for effective tool invocation.

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 coverage is 100%, but the description adds value by explaining that 'countries' should be comma-separated, detailing behavior of 'rolling' and 'trailing', and noting that 'indicator' is required and omitting it returns available indicators. It also warns against using 'tickers=', which is not in 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 'Labour and social metrics by country' and lists the available indicators, specifying the verb 'get' and resource 'metrics'. It distinguishes from siblings by focusing on jobs/society metrics while siblings cover other categories.

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 explicitly states required parameter usage ('Requires countries="United States"'), warns against using 'tickers=', and explains when to use parameters like start_date/end_date, quarterly, rolling, trailing. However, it does not directly compare against specific sibling tools for when to use alternatives.

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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