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JerBouma

Finance Toolkit

by JerBouma

jobs

Read-onlyIdempotent

Retrieve labour and social metrics by country, such as unemployment, poverty, and income inequality. Use countries= to compare multiple nations or add FRED-backed US payroll and jobless claims data.

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.2026-10-02
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.2021-10-03
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

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv2.2.1
    • changedInput schema / properties / end_date / default
      Previous value: -"2026-08-19"New value: +"2026-10-02"
    • changedInput schema / properties / start_date / default
      Previous value: -"2021-08-20"New value: +"2021-10-03"
  2. Changed4 schema fields changedv2.2.0
    • changedInput schema / properties / end_date / default
      Previous value: -"2026-07-14"New value: +"2026-08-19"
    • changedInput schema / properties / gmdb_source / description
      Previous value: -"Use the OECD Global Macro Data Bank as the data source when True."New value: +"Use 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."
    • changedInput schema / properties / indicator / enum
      Previous value: -[
      -  "get_income_inequality",
      -  "get_labour_productivity",
      -  "get_population_statistics",
      -  "get_poverty_rate",
      -  "get_unemployment_rate"
      -]New value: +[
      +  "get_income_inequality",
      +  "get_labour_productivity",
      +  "get_population_statistics",
      +  "get_poverty_rate",
      +  "get_unemployment_rate",
      +  "get_nonfarm_payrolls",
      +  "get_initial_jobless_claims"
      +]
    • changedInput schema / properties / start_date / default
      Previous value: -"2021-07-15"New value: +"2021-08-20"
  3. Changed5 schema fields changed
    • changedInput schema / properties / end_date / default
      Previous value: -"2026-07-09"New value: +"2026-07-14"
    • addedInput schema / properties / rolling
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "integer"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Rolling 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.",
      +  "title": "Rolling"
      +}
    • addedInput schema / properties / standardize
      Added value: +{
      +  "default": false,
      +  "description": "Return 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.",
      +  "title": "Standardize",
      +  "type": "boolean"
      +}
    • changedInput schema / properties / start_date / default
      Previous value: -"2021-07-10"New value: +"2021-07-15"
    • addedInput schema / properties / trailing
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "integer"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Trailing 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.",
      +  "title": "Trailing"
      +}
  4. Changed2 schema fields changedv2.1.4
    • changedInput schema / properties / end_date / default
      Previous value: -"2026-06-27"New value: +"2026-07-09"
    • changedInput schema / properties / start_date / default
      Previous value: -"2021-06-28"New value: +"2021-07-10"
  5. Changed2 schema fields changedv2.1.3
    • changedInput schema / properties / end_date / default
      Previous value: -"2026-06-23"New value: +"2026-06-27"
    • changedInput schema / properties / start_date / default
      Previous value: -"2021-06-24"New value: +"2021-06-28"
  6. Changed4 schema fields changedv0.1.2
    • changedInput schema / properties / end_date / default
      Previous value: -"2026-06-22"New value: +"2026-06-23"
    • removedInput schema / properties / rounding
      Removed value: -{
      -  "anyOf": [
      -    {
      -      "type": "integer"
      -    },
      -    {
      -      "type": "null"
      -    }
      -  ],
      -  "default": null,
      -  "description": "Number of decimal places to round results to.",
      -  "title": "Rounding"
      -}
    • addedInput schema / properties / show_columns
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "description": "Comma-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.",
      +  "title": "Show Columns"
      +}
    • changedInput schema / properties / start_date / default
      Previous value: -"2021-06-23"New value: +"2021-06-24"
  7. Addedv0.1.1

TDQS

A4/5.0
Behavior4/5

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

Annotations already cover the read-only/idempotent profile, and the description adds non-obvious behavior beyond them: two indicators require a FRED API key and return only a 'United States' column regardless of countries=, and gmdb_source switches to an independent provider with different coverage. That is meaningful operational context the annotations do not supply.

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?

It is front-loaded with the resource and the hard 'countries=' requirement, then the indicator list, and closes with the FRED caveat. The only mild redundancy is restating rolling/trailing behavior already in the schema, but the density is justified for a 13-parameter tool.

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?

With an output schema present, return formatting need not be explained, and the description covers the indicator set, source caveats, auth requirement and parameter behaviors. It is close to complete; adding a note on default date range behavior or the FRED-key failure mode would close the remaining gap.

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

Parameters3/5

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

Schema coverage is 100%, so the schema already documents lag, growth, period, rolling, trailing, dates, countries, quarterly, standardize and show_columns. The description reinforces rolling/trailing semantics and the countries requirement but adds no syntax or format detail beyond the schema, so the baseline of 3 applies.

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 description states a specific resource ('Labour and social metrics by country') and enumerates the exact indicators available, so the agent knows what content lives behind the generic name 'jobs'. It also draws a boundary against ticker-based tools ('Do NOT use tickers='), though it does not distinguish itself from close siblings like 'macroeconomics' or 'government'.

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?

It gives explicit usage constraints: 'Requires countries=United States', comma-separated multi-country syntax, and an exclusion ('Do NOT use tickers= for this tool'). What it lacks is guidance on when to prefer this tool over the government/macroeconomics siblings, so it is clear context without full routing logic.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.