Calculate Compound Annual Growth Rate (CAGR), real inflation-adjusted purchasing power (Fisher effect), and exact investment doubling horizon.
| Name | Required | Description | Default |
|---|---|---|---|
| finalValue | Yes | Ending portfolio / asset valuation ($) | |
| initialValue | Yes | Beginning portfolio / asset valuation ($) | |
| periodsYears | Yes | Duration in years | |
| inflationRatePercent | No | Annualized expected inflation rate % |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full disclosure burden. It does reveal that the tool calculates three distinct financial quantities and references the Fisher effect, which is useful, but it does not specify return format, whether all results are returned together, or assumptions such as constant annual growth or compounding frequency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that lists the tool's core outputs without filler. Every phrase adds information, and the structure makes the tool's purpose immediately readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, so the description needs to convey sufficient context for an agent to know what results to expect. It names the outputs but does not explain the return structure, calculation assumptions, edge cases, or how the optional inflation parameter affects the real purchasing-power result, leaving meaningful gaps for a numeric calculator.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters themselves are already documented with defaults and units. The description adds no additional parameter-level meaning or relationships among initialValue, finalValue, periodsYears, and inflationRatePercent, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description names a clear verb, 'Calculate,' and specific financial outputs: CAGR, inflation-adjusted purchasing power via the Fisher effect, and investment doubling horizon. It is more specific than a generic growth tool and should help an agent distinguish it from broad siblings like compound_wealth, though it bundles three outputs rather than one focused resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states what the tool computes but gives no guidance on when to choose it over siblings such as compound_wealth, sip_investment, or npv_irr. There are no explicit conditions, exclusions, or alternative routing hints, so the agent must infer usage from the metric names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly separated by domain and target calculation, such as rocket_deltav versus projectile_motion or black_scholes versus compound_wealth. A few pairs like home_loan_emi/mortgage_piti and contractor_parity/billable_floor could be initially confused, but the descriptions resolve the intended use cases.
All tool names are lowercase snake_case and generally follow a topic-plus-suffix pattern, which is readable and consistent. The pattern is not a strict verb_noun convention, and acronym-heavy names like feie_nomad_tracker, scorp_optimizer, and casio_991_solve introduce stylistic variance.
At exactly 25 tools, this is at the heavy but still usable end of the scale. The broad spread across tax, finance, engineering, physics, math, and cloud cost makes the server feel more like several domain calculators merged into one service.
Each tool is a self-contained calculation with no missing follow-up operations, so there are no obvious dead ends for the workflows it targets. The main gaps are minor adjacent calculators—such as NPV, depreciation, or broader statistical inference—that agents could work around or obtain elsewhere.
