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JerBouma

Finance Toolkit

by JerBouma

liquidity

Read-onlyIdempotent

Compute liquidity ratios (current, quick, cash, working capital) for any ticker to assess short-term financial health. Supports quarterly data and custom date ranges.

Instructions

Pre-computed liquidity ratios (current ratio, quick ratio, cash ratio, working capital). Requires tickers='AAPL' — use comma-separated values for multiple tickers. Use instead of raw financial statements. Supports quarterly=true and start_date/end_date.

Available indicators: get_current_ratio, get_quick_ratio, get_cash_ratio, get_working_capital, get_operating_cash_flow_ratio, get_operating_cash_flow_sales_ratio, get_short_term_coverage_ratio, get_defensive_interval_ratio.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lagNoNumber of periods to lag when computing growth rates.
daysNoNumber of calendar days used in day-count-based calculations.
growthNoReturn period-over-period growth rates instead of absolute values.
tickersNoComma-separated ticker symbols, e.g. 'AAPL,MSFT,GOOGL'.
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.
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
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.
benchmark_tickerNoTicker used as the market benchmark, e.g. 'SPY' or '^GSPC'.SPY

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already indicate readOnly, idempotent, and openWorld, so the description doesn't need to restate safety. It adds useful behavioral details such as returning the list of indicators when omitted, behavior of standardize and growth parameters, and how show_columns affects output, which goes 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.

Conciseness5/5

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

The description is a single, well-structured sentence that covers key facts: what it provides, the required tickers, and the available indicators. It avoids redundancy and is easy to parse, with the parameter list neatly embedded in the schema.

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 there is no explicit output schema, the description sufficiently conveys what to expect: pre-computed ratios, options for standardization/growth, and filtering via show_columns. It also informs about placeholder behavior when indicator is omitted. Missing details like exact output format are not critical for tool selection.

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 provides 100% coverage with detailed descriptions for every parameter. The description supplements this with practical examples (e.g., comma-separated tickers, quarterly=true, start_date/end_date) and clarifies that indicator is required, adding value beyond the schema's generic text.

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 pre-computed liquidity ratios, lists the specific indicators available (current, quick, cash, working capital, etc.), and distinguishes it from raw financial statements. This clearly defines the tool's purpose and sets it apart from other ratio-focused tools.

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 advises using this tool instead of raw financial statements and explains required parameters (indicator) and optional ones (tickers, quarterly, date range). However, it doesn't explicitly contrast with sibling ratio tools like profitability or solvency, though the name and indicator list make the use case clear.

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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