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JerBouma

Finance Toolkit

by JerBouma

momentum

Read-onlyIdempotent

Calculate momentum technical indicators like RSI, MACD, and stochastic oscillator for any stock ticker automatically from price data.

Instructions

Momentum technical indicators (RSI, MACD, Stochastic Oscillator, Williams %R, Aroon). Applied to price data automatically — no need to fetch prices first. Requires tickers='AAPL' — use comma-separated values for multiple tickers.

Available indicators: get_money_flow_index, get_williams_percent_r, get_aroon_indicator, get_commodity_channel_index, get_relative_vigor_index, get_force_index, get_ultimate_oscillator, get_percentage_price_oscillator, get_detrended_price_oscillator, get_average_directional_index, get_chande_momentum_oscillator, get_ichimoku_cloud, get_stochastic_oscillator, get_moving_average_convergence_divergence, get_relative_strength_index, get_balance_of_power.

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'.
constantNoValue for constant.
end_dateNoEnd of the date range in YYYY-MM-DD format.2026-07-14
window_1NoValue for window_1.
window_2NoValue for window_2.
window_3NoValue for window_3.
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
base_windowNoValue for base_window.
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.
smooth_widowNoValue for smooth_widow.
signal_windowNoValue for signal_window.
benchmark_tickerNoTicker used as the market benchmark, e.g. 'SPY' or '^GSPC'.SPY
conversion_windowNoValue for conversion_window.
lead_span_b_windowNoValue for lead_span_b_window.

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, idempotentHint, and openWorldHint. Description adds valuable context: 'Applied to price data automatically — no need to fetch prices first,' which clarifies the workflow. No contradictions.

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?

Two concise paragraphs: first gives purpose and key usage note, second lists all indicators. Front-loaded with critical information. Could be slightly more structured but efficient overall.

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?

Description provides sufficient context for a complex tool with 24 parameters. It explains the core functionality (momentum indicators), automation benefit, and lists all indicators. Output schema exists to cover return values, so description doesn't need to.

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 coverage is 100% with all parameters described. Description adds extra meaning: 'indicator' omission returns available list, tickers format example, and some default parameter values. This improves usability beyond schema alone.

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?

Description clearly states it computes momentum technical indicators (RSI, MACD, etc.) and emphasizes automatic application to price data. It distinguishes from sibling tools focused on other financial metrics like profitability or valuation.

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?

Description indicates required tickers parameter and lists available indicators, but provides no explicit guidance on when to use this tool versus siblings or when not to use it. Usage context is implied by tool name and indicator list.

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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