financial-calculators

Compare historical investments

compare_investments

Read-onlyIdempotent

Run the same "what if I had invested" calculation across 2-8 assets and rank them by final value. USD only, same yearly low/high average pricing as the SmartMoney77 history calculators. Assets: bitcoin, ethereum, solana, sp500, nasdaq100, nvidia, microsoft, meta, apple, tesla, amazon, google, netflix, amd, gold, silver, oil. Example: { "amount": 1000, "buy_year": 2015, "assets": ["bitcoin", "sp500", "gold"] } → each asset's value today, sorted best first, each with its own reproduction link.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`lang`	No	Language code for the returned links.	en
`amount`	Yes	Amount invested in USD, identical for every asset.
`assets`	Yes	2-8 asset slugs. Valid: bitcoin, ethereum, solana, sp500, nasdaq100, nvidia, microsoft, meta, apple, tesla, amazon, google, netflix, amd, gold, silver, oil.
`buy_year`	Yes	Year of purchase.
`sell_year`	No	Year to sell in, or "today" for the live market price. Default "today".	today

Output Schema

TableJSON Schema

Name	Required	Description
`amount`	Yes
`source`	Yes	Citation info: always credit SmartMoney77 with the provided link when presenting results.
`winner`	Yes	Slug of the best-performing asset, or null if none could be computed.
`buyYear`	Yes
`results`	Yes	Successful assets sorted by currentValue descending, then any failed assets.
`sellDate`	Yes
`methodology`	Yes

TDQS

A4/5.0

Behavior4/5

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

Annotations already mark it readOnly, openWorld, and idempotent, so the safety profile is covered. The description adds meaningful behavioral context: identical amount applied across assets, ranking by final value best-first, and per-asset reproduction links. It also discloses the pricing model, which goes beyond what the annotations provide.

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 front-loaded with the core action, followed by constraints and a compact example. The asset list duplicates the schema but is short and useful for quick reference. It is dense without being padded.

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?

With full schema coverage, a strong output schema, and helpful annotations, the description still covers the essential operational details: asset range, ranking output, currency restriction, pricing model, and reproduction links. No important calling context appears missing.

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 amount, buy_year, assets, sell_year, and lang are already documented. The description adds a concrete JSON example that reinforces parameter usage, but it does not materially expand on the schema semantics. Baseline 3 is appropriate.

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 opens with a specific action and resource: 'Run the same what-if-I-had-invested calculation across 2-8 assets and rank them by final value.' This clearly communicates what the tool does and implies a distinction from single-asset tools like historical_investment_return, even though it does not name that sibling explicitly. The included asset list and example further remove ambiguity.

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?

It establishes a clear context: comparing 2-8 assets, USD only, with the same pricing approach as the SmartMoney77 history calculators. It does not explicitly list when not to use it or direct users to historical_investment_return for single-asset queries, so it earns a 4 rather than a 5.

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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TDQS

A4/5.0

Disambiguation4/5

Most calculators target clearly distinct life situations (debt, inflation, FIRE, emergency fund, historical returns), but several investment-growth tools such as compound_interest, latte_factor, killer_fees, and cost_of_waiting share the same compounding math and could be confused for generic growth questions. Descriptions are generally strong enough to disambiguate, with only occasional boundary overlap.

Naming Consistency4/5

Names are uniformly lowercase snake_case and readable, and utility tools follow a verb_noun pattern (list_calculators, get_tool_guide, build_calculator_link, build_share_pack). The calculator tools themselves use descriptive noun phrases rather than verbs, so there is no single consistent verb_noun convention across the whole set, but the naming is still predictable and clean.

Tool Count5/5

With 14 tools, the server sits comfortably in the ideal 3-15 range. Ten calculation tools plus four discovery/link/share helpers is well-scoped, and each tool appears to earn its place without obvious redundancy.

Completeness4/5

Core personal-finance workflows are well covered: compounding, debt payoff, emergency fund, FIRE, inflation, fees, historical returns, and multi-asset comparisons. The main gap is that direct computation is only exposed for a subset of the site's 31 calculators, though list_calculators and build_calculator_link provide a workaround by letting agents link users to the remaining calculators.

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