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JerBouma

Finance Toolkit

by JerBouma

breadth

Read-onlyIdempotent

Measure market breadth using indicators like McClellan Oscillator, OBV, and TRIN, computed automatically from price data.

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.

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.
tickersNoComma-separated ticker symbols, e.g. 'AAPL,MSFT,GOOGL'.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-07-14
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
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.
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.
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
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, and idempotentHint. The description adds transparency by stating the tool applies to price data automatically (no prior fetch needed), which is valuable beyond annotations. No destructive behavior is implied, and no contradictions with annotations exist.

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 concise, with two paragraphs. The first paragraph covers purpose, key requirement (tickers), and automatic behavior. The second paragraph lists indicators. No unnecessary sentences, and all content is relevant and front-loaded.

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?

With 17 parameters, 1 required, and an output schema present, the description adequately covers the tool's purpose and key usage. It explains the automatic price data aspect and ticker requirement. However, it does not describe the output format (though presumably covered by output schema). Given the complexity, it is sufficiently complete.

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 the baseline is 3. The description adds value by explaining the 'indicator' parameter's default behavior (returns list if omitted) and the format for 'tickers' (comma-separated). For other parameters, it does not add much beyond schema, but the additional context for key parameters justifies a 4.

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 clearly states the tool provides market breadth technical indicators, lists examples (McClellan Oscillator, OBV, etc.), and specifies it's applied automatically to price data. It distinguishes itself from siblings by focusing specifically on breadth indicators, which are not covered by other tools like 'efficiency' or 'momentum'.

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 explains when to use the tool (when needing breadth indicators) and mentions prerequisites like requiring tickers. It does not explicitly exclude cases or name alternatives, but the context of sibling tools in other categories implies when not to use it. The guidance on tickers and indicator selection is clear but could be more explicit about exclusivity.

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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