calculate_cagrCalculate the Compound Annual Growth Rate (CAGR) of an investment.
Args:
initial_value: Initial investment in rupees.
final_value: Final value in rupees.
years: Holding period in years.
| Name | Required | Description | Default |
|---|---|---|---|
| years | Yes | ||
| final_value | Yes | ||
| initial_value | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the safety profile (readOnlyHint true, destructive false), so the description only needs to add behavioral context. It adds parameter meaning but does not disclose formula assumptions, edge cases, or output form; it does not contradict the annotations.
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 one focused purpose sentence followed by a compact Args list. The essential fact is front-loaded, and each argument line earns its place by supplying the units that the schema lacks.
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?
For a simple, read-only calculation with three documented inputs, the description is sufficient for an agent to select and invoke it. The only notable omission is that there is no output schema and the description does not state whether the result is returned as a decimal or percentage.
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?
The schema has 0% description coverage, so the description is the sole semantic source for parameters. It defines initial_value as 'Initial investment in rupees', final_value as 'Final value in rupees', and years as 'Holding period in years', covering every required parameter with meaningful units.
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 specific verb and resource: 'Calculate the Compound Annual Growth Rate (CAGR) of an investment.' This is clear and identifiable against siblings like calculate_sip or calculate_emi, but it never explicitly contrasts itself with those alternatives.
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?
Usage is implied by the tool's purpose—if an agent needs an annualized growth rate from initial, final, and years, this is the tool. There is no explicit guidance about when to prefer it over related calculators, and no exclusion criteria.
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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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.
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.
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.
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.