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JerBouma

Finance Toolkit

by JerBouma

breadth

Read-onlyIdempotent

Compute market technical indicators like McClellan Oscillator, On-Balance Volume, and Advance/Decline Line directly from price data, eliminating the need to fetch prices separately.

Instructions

Market breadth technical indicators (McClellan Oscillator, OBV, Advance/Decline Line, Chaikin). Applied to price data automatically — no need to fetch prices first. Requires tickers='AAPL' — use comma-separated values for multiple tickers.

Available indicators: get_mcclellan_oscillator, get_advancers_decliners, get_on_balance_volume, get_accumulation_distribution_line, get_chaikin_oscillator, get_trin, get_new_highs_new_lows, get_chaikin_money_flow, get_ease_of_movement, get_negative_volume_index, get_positive_volume_index.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lagNoNumber of periods to lag when computing growth rates.
growthNoReturn period-over-period growth rates instead of absolute values.
periodNoObservation frequency, e.g. 'monthly', 'quarterly', or 'annual'.daily
windowNoValue for window. Leave unset to use the default of the indicator you selected. Defaults are 14 for get_ease_of_movement; 20 for get_chaikin_money_flow; 252 for get_new_highs_new_lows.
tickersNoComma-separated ticker symbols, e.g. 'AAPL,MSFT,GOOGL'.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-08-19
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
long_windowNoValue for long_window.
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.
start_valueNoValue for start_value.
close_columnNoValue for close_column.Adj Close
short_windowNoValue for short_window.
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.
volume_divisorNoValue for volume_divisor.
long_ema_windowNoValue for long_ema_window.
benchmark_tickerNoTicker used as the market benchmark, e.g. 'SPY' or '^GSPC'.SPY
short_ema_windowNoValue for short_ema_window.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Beyond the readOnlyHint annotation, the description explains that the tool automatically applies to price data, which is a behavioral detail. It does not discuss rate limits, error handling, or output structure, but the read-only and idempotent hints already cover the main expectations.

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 compact and front-loaded with the purpose. The list of indicators is somewhat redundant with the enum in the schema, but it is brief and does not overwhelm. The two paragraphs are well-structured and to the point.

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's complexity (19 parameters), the description does not explain the meanings of many parameters (e.g., short_window, standardize, volume_divisor) or the output format. However, the schema descriptions compensate, so the description is minimally sufficient but not comprehensive.

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?

The schema already provides detailed descriptions for all parameters (100% coverage). The description adds limited extra value by clarifying that tickers should be comma-separated and by listing the available indicator names, but it does not explain windows, standardization, or other nuances beyond the schema.

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 that this tool provides market breadth technical indicators and lists several examples (e.g., McClellan Oscillator, OBV). It distinguishes the category from sibling tools like momentum or liquidity by naming the indicator family, though it does not explicitly contrast with alternatives.

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?

It gives a key usage hint that price data is automatically handled ('no need to fetch prices first') and specifies that tickers should be provided. However, it does not mention when not to use this tool or mention alternative tools, leaving some ambiguity about selection among sibling indicators.

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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