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retirement_calc

Calculate your retirement savings growth and project your nest egg based on age, savings, contributions, and expected return.

Instructions

Calculate retirement savings growth and projected nest egg.

Parameters:
    current_age — Current age in years.
    retirement_age — Target retirement age.
    savings — Current retirement savings.
    monthly_contribution — Monthly contribution (default: 0).
    rate — Expected annual return (default: 7.0).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
current_ageYes
retirement_ageYes
savingsYes
monthly_contributionNo
rateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It only states 'Calculate retirement savings growth' without disclosing important behavioral traits such as compounding frequency, whether inflation is considered, or that the result is a future value projection. The tool's behavior is implied but not explicit.

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 concise with one sentence for purpose followed by a parameter list. Each parameter gets a brief explanation, but the list largely mirrors the schema property names, making it somewhat redundant. Overall efficient but could be more integrated.

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

Completeness2/5

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

With an output schema likely present, the description should explain what the tool returns beyond 'projected nest egg'. It does not mention whether output includes yearly breakdown, graph, or additional metrics. This lack of detail makes it less complete for an agent to understand the tool's full behavior.

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?

The description adds meaningful context beyond the schema by specifying units (e.g., 'in years') and default values (e.g., monthly_contribution defaults to 0, rate to 7.0). This helps the agent interpret parameters correctly. However, it does not clarify constraints like valid age ranges or allowed rate limits.

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 clearly states the verb 'Calculate' and the resource 'retirement savings growth and projected nest egg', giving a precise purpose. However, it does not differentiate from similar sibling tools like 'savings_goal_calc' or 'investment_calculator', missing an opportunity to clarify its unique scope.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like compound_interest or savings_goal_calc. It lacks context on prerequisites, limitations, or the type of retirement calculation performed (e.g., assumes constant rate, monthly compounding).

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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