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JerBouma

Finance Toolkit

by JerBouma
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

rates

Read-onlyIdempotent

Retrieve central bank policy rates, government bond yields, and corporate bond spreads for multiple countries. Filter by date range and frequency.

Instructions

Interest rate data (central bank policy rates, short/long-term rates, government bond yields, ICE BofA corporate bond series, EURIBOR, ECB rates, Federal Reserve rates). 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.

Available indicators: get_central_bank_policy_rate, get_short_term_interest_rate, get_long_term_interest_rate, get_government_bond_yield, get_euribor_rates, get_european_central_bank_rates, get_federal_reserve_rates, get_ice_bofa_effective_yield, get_ice_bofa_option_adjusted_spread, get_ice_bofa_total_return, get_ice_bofa_yield_to_worst.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lagNoNumber of periods to lag when computing growth rates.
rateNoValue for rate.
growthNoReturn period-over-period growth rates instead of absolute values.
periodNoObservation frequency, e.g. 'monthly', 'quarterly', or 'annual'.
nominalNoValue for nominal.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-06-27
maturityNoValue for maturity.
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.
maturitiesNoComma-separated bond maturity labels, e.g. '3month,2year,10year'.
short_termNoValue for short_term.
start_dateNoStart of the date range in YYYY-MM-DD format.2021-06-28
gmdb_sourceNoUse the OECD Global Macro Data Bank as the data source when True.
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

Tool Definition Quality

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint. The description adds behavioral context such as requiring countries and supporting date filtering, without contradicting annotations. It could mention return structure but has output schema.

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 well-structured with two paragraphs: first describing the data, second providing usage instructions and a compact list of indicators. It is front-loaded and efficient, though slightly verbose with the full indicator list.

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 15 parameters and an output schema, the description covers key usage guidance (countries, tickers, date range, quarterly, indicator list). It is complete for an agent to invoke tool correctly, though some less common parameters (e.g., lag, growth) are not elaborated.

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 coverage is 100%, so baseline is 3. The description adds value beyond the schema by explaining the countries parameter format, noting the indicator's behavior when omitted, and listing all available indicators explicitly.

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 explicitly states the tool provides 'Interest rate data' and lists specific series (central bank rates, bond yields, etc.). It clearly identifies the resource and distinguishes it from sibling tools like 'fixed_income' 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 Guidelines5/5

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

The description gives explicit usage instructions: 'Requires countries='United States'', 'Do NOT use tickers= for this tool', and 'Supports start_date/end_date and quarterly=true'. It also notes that omitting the required indicator returns a list, preventing misuse.

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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