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JerBouma

Finance Toolkit

by JerBouma

efficiency

Read-onlyIdempotent

Compute key efficiency ratios such as asset turnover, inventory turnover, and cash conversion cycle for specified tickers. Avoids need for raw financial statements.

Instructions

Pre-computed efficiency ratios (asset turnover, inventory turnover, days sales outstanding, days payable outstanding, cash conversion cycle). 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_days_of_inventory_outstanding, get_days_of_sales_outstanding, get_operating_cycle, get_days_of_accounts_payable_outstanding, get_cash_conversion_cycle, get_cash_conversion_efficiency, get_receivables_turnover, get_inventory_turnover_ratio, get_accounts_payables_turnover_ratio, get_sga_to_revenue_ratio, get_fixed_asset_turnover, get_asset_turnover_ratio, get_operating_ratio, get_research_and_development_ratio, get_selling_and_marketing_ratio, get_general_and_administrative_ratio, get_stock_based_compensation_ratio, get_deferred_revenue_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.2026-07-14
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.2021-07-15
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
Behavior3/5

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

Annotations (readOnlyHint, openWorldHint, idempotentHint) already disclose safety and idempotency. The description adds that it is 'pre-computed' and lists available indicators, but does not elaborate on error behavior, rate limits, or return format. It provides minimal additional behavioral context beyond 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 concise (two sentences plus a list) and front-loads the core purpose. It is efficient but could be more structured (e.g., bullet points for parameters). No wasted sentences.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 12 parameters and an output schema, the description covers only the most basic (tickers, quarterly, dates). It does not explain advanced parameters like 'lag', 'growth', 'trailing', 'standardize', 'show_columns', or 'benchmark_ticker'. Output schema exists, so return values need not be explained, but completeness is moderate.

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 description coverage is 100%, so baseline is 3. The description mentions 'tickers', 'quarterly', 'start_date/end_date', but the schema already describes these adequately. It does not add significant new meaning for parameters like 'lag', 'days', 'growth', etc.

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 provides 'Pre-computed efficiency ratios' and lists specific ratios. It distinguishes from sibling tools by focusing on efficiency metrics (vs. profitability, liquidity, etc.), but does not explicitly differentiate. The verb 'provides' and the resource 'efficiency ratios' are clear.

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

Usage Guidelines3/5

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

The description gives usage context: 'Requires tickers='AAPL'', 'Use instead of raw financial statements', and notes support for quarterly and date parameters. However, it does not specify when not to use it or provide explicit alternatives among sibling tools.

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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