SmartFin

Compare lump sum, monthly and buy-the-dip

smartfin_compare_investment_strategies

Read-onlyIdempotent

Runs one amount through three ways of buying the same US stock or index ETF over a chosen period, on real daily closing prices (adjusted for splits and reinvested dividends): all at once on the first trading day (lump sum), spread evenly on the trading day nearest the 1st of each month, or bought after the price falls a set % from its latest high. Returns each strategy's final value, total and yearly return, worst fall and Sharpe ratio. Use when the user asks which way of investing would have done better for a specific stock or index over a past period, or what an amount would be worth under each approach. Do not use for one strategy only (use smartfin_calculate_investment_return), for several reference periods at once (use smartfin_compare_time_periods), or for future projections. Limits: US-listed S&P 500 companies and major index ETFs only, prices in US dollars, month-level start and end; results depend on the period and are not a prediction.

Input Schema

TableJSON Schema

Name	Required	Description
`amount`	Yes	Total dollars to invest across the whole period
`ticker`	Yes	Stock or ETF symbol, not a company name: AAPL not Apple. Covers 508 symbols: the S&P 500 companies plus the index ETFs SPY, VOO, IVV, QQQ, DIA, IWM, VTI.
`end_month`	No	Last month to include, YYYY-MM. Omit for the latest available month
`start_month`	Yes	First month, YYYY-MM, e.g. 2016-01
`response_format`	No	detailed adds worst fall and Sharpe ratio to the summary. Default concise
`dip_threshold_pct`	No	Buy-the-dip trigger: a fall of this % from the latest high. Default 10
`dip_percent_per_buy`	No	Share of the amount spent on each dip, in %. Default 10

Output Schema

TableJSON Schema

Name	Required	Description
`cite`	Yes	How to credit this result
`data`	Yes
`next`	Yes	Suggested follow-up calls
`links`	Yes
`how_to`	Yes	Steps for the user to see or redo this on smartfin.fyi
`source`	Yes
`summary`	Yes	Plain-language result the assistant can quote

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 29, 2026

addedOutput schema / properties / links / properties / page

Added value: +{
+  "description": "SmartFin's page for this stock, when it has one",
+  "type": "string"
+}

First observedSep 29, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, non-open-world behavior, so the safety profile is covered. The description adds genuinely useful context beyond that: the pricing basis (daily closes adjusted for splits and reinvested dividends), the coverage limits (US-listed S&P 500 names plus major ETFs, USD, month-level granularity), and an explicit caveat that results are period-dependent and not a prediction.

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?

Purpose and the three strategies are front-loaded before the usage guidance, and every sentence carries information. It is on the long side for a single paragraph, but the length is justified by three distinct strategies plus sibling routing; no filler sentences.

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

Completeness5/5

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

For a 7-parameter analytical tool with an output schema present, the description covers methodology, universe constraints, granularity, usage routing, and interpretation caveats. An agent has everything needed to select and invoke it correctly without needing return-value details, since the output schema supplies those.

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%, so the baseline is 3, but the description adds real meaning by defining what each strategy does — lump sum on the first trading day, monthly on the trading day nearest the 1st, and buy-the-dip after a set % fall from the latest high — which is exactly the semantics behind dip_threshold_pct and dip_percent_per_buy that the schema only names.

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?

States a specific verb (runs one amount through three buying strategies) and resource (US stock/index ETF over a period), and explicitly differentiates from siblings by naming smartfin_calculate_investment_return and smartfin_compare_time_periods. The three strategies are enumerated concretely, so an agent knows exactly what is computed.

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

Usage Guidelines5/5

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

Gives explicit when-to-use ('user asks which way of investing would have done better for a specific stock or index over a past period') and when-not-to-use cases with named alternatives for single-strategy and multi-period comparisons, plus an exclusion for future projections. Nothing is left to inference.

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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