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FinanceGenius.AI

Calculate FD maturity

calculate_fd_maturity
Read-only

Calculate FD maturity amount with compounding.

    Args:
        deposit_amount: Principal deposit in rupees.
        annual_rate: Annual interest rate as a percentage.
        years: FD tenure in years (e.g. 1.5 for 18 months).
        compounding: One of 'monthly', 'quarterly', 'half_yearly', 'yearly'.
                     Most Indian FDs compound quarterly.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearsYes
annual_rateYes
compoundingNoquarterly
deposit_amountYes

TDQS

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is known. The description adds useful domain behavior through the compounding options and the note that quarterly compounding is the Indian FD norm, but does not disclose return format or edge cases. This is adequate given the simple, side-effect-free nature of the tool.

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?

The description is a compact, well-structured docstring with a clear one-line summary followed by a concise Args section. Every line adds valuable information with no redundancy or fluff.

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 pure calculation tool with no output schema and four parameters, the description covers all inputs, their types, units, and domain conventions. The return value (maturity amount) is directly implied by the purpose statement, and the read-only annotations cover side-effect concerns. An agent has enough information to invoke this tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry parameter meaning, and it does. It explains each parameter with units (rupees, percentage), a format example (1.5 for 18 months), and the allowed values plus default for compounding. This fully compensates for the missing schema descriptions.

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?

The description states a specific verb ('Calculate'), the resource ('FD maturity amount'), and the key mechanism ('with compounding'). It is clearly distinguishable from sibling calculation tools like calculate_emi or calculate_cagr, which target different financial products.

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

Usage Guidelines3/5

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

The description implies its use case through its name and explicit calculation purpose, and it adds practical context ('Most Indian FDs compound quarterly'). However, it does not explicitly state when to prefer this tool over alternatives such as find_best_fd or calculate_sip, nor does it mention exclusions.

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

A4.3/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: the calculate_* tools cover different financial formulas, find_best_* tools recommend different product types, and search/get/compare form a coherent product workflow. There is no realistic ambiguity between tools despite the overlap in financial domain.

Naming Consistency5/5

Tool names consistently follow a verb-first snake_case pattern, with clear groupings like calculate_*, find_best_*, and get_*. Minor use of abbreviations like CAGR and EMI is natural and does not break the naming convention.

Tool Count5/5

12 tools is well-scoped for a personal finance assistant covering calculators, product search, product details, comparisons, recommendations, and concept explanations. Each tool earns its place without redundancy or bloat.

Completeness4/5

The tool set covers core financial calculations, product discovery, comparison, recommendations, and educational explanations, which is strong for the stated purpose. Minor gaps exist around loan/insurance product comparisons and more advanced investment planning, but agents can accomplish most typical finance workflows.

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