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JerBouma

Finance Toolkit

valuation

Read-onlyIdempotent

Retrieve key valuation ratios like P/E, EPS, EV/EBITDA, and market cap for any ticker. Supports multiple tickers, quarterly or annual data, and a range of indicators.

Instructions

Pre-computed valuation ratios (P/E, EPS, EV/EBITDA, EV/EBIT, P/B, P/S, PEG, dividend yield, FCF yield, market cap). 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_earnings_per_share, get_revenue_per_share, get_price_to_earnings_ratio, get_price_to_earnings_growth_ratio, get_book_value_per_share, get_price_to_book_ratio, get_interest_debt_per_share, get_capex_per_share, get_earnings_yield, get_dividend_payout_ratio, get_dividend_yield, get_weighted_dividend_yield, get_price_to_cash_flow_ratio, get_price_to_free_cash_flow_ratio, get_market_cap, get_enterprise_value, get_ev_to_sales_ratio, get_ev_to_ebit, get_ev_to_ebitda_ratio, get_ev_to_operating_cashflow_ratio, get_tangible_asset_value, get_net_current_asset_value.

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.
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.
show_dailyNoValue for show_daily.
start_dateNoStart of the date range in YYYY-MM-DD format.2021-06-28
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
include_dividendsNoValue for include_dividends.
use_ebitda_growth_rateNoValue for use_ebitda_growth_rate.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint as true. The description adds behavioral context such as 'Pre-computed' and the ability to list indicators by omitting the 'indicator' parameter. No contradictions with annotations.

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 front-loaded with the core purpose and is relatively concise. The list of indicators could be considered redundant with the schema enum, but it is still helpful. Overall, it is efficient without unnecessary fluff.

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 complexity (14 parameters, many optional) and the presence of an output schema, the description covers the essential usage (tickers, indicator, quarterly, date range). It does not explain every parameter, but the schema fills those gaps. The description is complete enough for an AI agent to understand the tool's primary function and key configuration.

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 value by explaining the tickers format (comma-separated), the indicator selection (list provided), and the quarterly/date range support. While many parameters are only documented in the schema, the description still provides useful context beyond defaults.

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 that the tool provides 'Pre-computed valuation ratios' and lists examples (P/E, EPS, EV/EBITDA, etc.). It also clarifies that the tool should be used 'instead of raw financial statements' and requires tickers. This clearly distinguishes it from sibling tools like 'efficiency' or 'profitability'.

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 mentions support for quarterly data and date ranges. However, it does not explicitly compare to sibling tools or provide when-not-to-use scenarios. The context is clear but lacks exclusions.

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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