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JerBouma

Finance Toolkit

models

Read-onlyIdempotent

Calculate pre-computed financial models like WACC, DuPont analysis, Altman Z-Score, and intrinsic value for any ticker.

Instructions

Pre-computed financial models (WACC, DuPont analysis, Altman Z-Score, Piotroski F-Score, intrinsic value/DCF). Requires tickers='AAPL' — use comma-separated values for multiple tickers. Supports quarterly=true and start_date/end_date.

Available indicators: get_altman_z_score, get_dupont_analysis, get_enterprise_value_breakdown, get_extended_dupont_analysis, get_gorden_growth_model, get_intrinsic_valuation, get_piotroski_score, get_present_value_of_growth_opportunities, get_weighted_average_cost_of_capital.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lagNoNumber of periods to lag when computing growth rates.
growthNoReturn period-over-period growth rates instead of absolute values.
dilutedNoValue for diluted.
periodsNoValue for periods.
tickersNoComma-separated ticker symbols, e.g. 'AAPL,MSFT,GOOGL'.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-06-27
trailingNoNumber of trailing periods for rolling-window calculations.
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.2021-06-28
growth_rateNoAssumed constant growth rate as a decimal.
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.
cash_flow_typeNoValue for cash_flow_type.Free Cash Flow
rate_of_returnNoValue for rate_of_return.
calculate_dailyNoValue for calculate_daily.
project_periodsNoValue for project_periods.
benchmark_tickerNoTicker used as the market benchmark, e.g. 'SPY' or '^GSPC'.SPY
include_dividendsNoValue for include_dividends.
show_full_resultsNoValue for show_full_results.
perpetual_growth_rateNoTerminal (perpetual) growth rate used in DCF models.
weighted_average_cost_of_capitalNoWACC as a decimal, e.g. 0.09 for 9 %.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds the listing of available indicators and states 'Pre-computed', implying static results, which aligns with idempotent behavior. It does not contradict annotations but adds little beyond what is provided.

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 short, front-loads the purpose, and lists indicators in a clear manner. It uses two sentences plus a list, making it easy to scan. No unnecessary words.

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 the tool has many parameters (21) but schema covers them all, and an output schema exists, the description adequately covers the key usage points (tickers, quarterly, date range, indicator list). It could mention more about the meaning of optional parameters like lag or growth, but those are covered in the schema.

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 description coverage is 100%, so baseline is 3. The description adds actionable guidance on key parameters: 'Requires tickers='AAPL'' and 'Supports quarterly=true and start_date/end_date', which helps agents use the tool effectively.

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 clearly states it computes financial models (WACC, DuPont, etc.) and lists specific indicators. It is specific about the resource (financial models) but does not explicitly differentiate from sibling tools like valuation or profitability, though the listed models are unique.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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

The description mentions tickers requirement and support for quarterly and date range, but it provides no guidance on when to use this tool versus alternatives (e.g., when to use get_altman_z_score vs. a different tool). No exclusions or comparisons are given.

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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