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SmartFin

Inflation impact over time

smartfin_calculate_inflation_impact
Read-onlyIdempotent

What an amount will be worth in today's money after years of inflation at a fixed yearly rate, and what something costing that amount today will cost then. Use for questions about buying power or future prices at an assumed inflation rate. Do not use for historical CPI lookups: this uses one fixed rate, not official index data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearsYesNumber of years
amountYesAmount in dollars
annual_inflation_pctYesYearly inflation rate in %, e.g. 3

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
citeYesHow to credit this result
dataYes
nextYesSuggested follow-up calls
linksYes
how_toYesSteps for the user to see or redo this on smartfin.fyi
sourceYes
summaryYesPlain-language result the assistant can quote

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedOutput schema / properties / links / properties / page
      Added value: +{
      +  "description": "SmartFin's page for this stock, when it has one",
      +  "type": "string"
      +}
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the bar is lower. The description adds genuinely useful model semantics: a single fixed yearly rate rather than official index data, which is the key caveat an agent must not misrepresent. It stops short of describing the dual return values, though the output schema carries that.

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?

Two sentences, front-loaded with the computation and followed by usage and exclusion. Every clause earns its place with no redundancy.

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 an output schema, full parameter coverage, and annotations in place, the description only needs to add assumptions and routing. It does exactly that by stating the fixed-rate model and the CPI exclusion, leaving nothing an agent needs 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 the schema fully documents all three parameters including units ('Yearly inflation rate in %, e.g. 3'). The description restates the fixed-rate nature and the amount's role but adds no syntax or format detail beyond the schema, making the baseline 3 appropriate.

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 precise computation: it converts an amount backward to today's buying power and forward to a future price, both at a fixed annual rate. The verb+resource is unambiguous and clearly distinct from the sibling calculators (loan payment, FIRE number, savings growth).

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?

Explicitly names the use case ('buying power or future prices at an assumed inflation rate') and an exclusion ('Do not use for historical CPI lookups: this uses one fixed rate, not official index data'). The when and the when-not are both stated, so the agent can route confidently.

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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