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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the tool is known to be a safe, non-mutating operation. The description adds valuable behavioral context beyond annotations by specifying the return payload: monthly EMI, total interest, total payment, and a year-by-year amortisation schedule. This clarifies the calculation scope and output shape that the agent would otherwise need to discover at runtime.

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 compact and well-organized with a one-line summary plus structured Args/Returns sections. Every sentence earns its place: the purpose is front-loaded, parameters are documented with examples, and return values are listed without padding. There is no redundant or vague prose.

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 tool with three parameters and no output schema, the description is fully self-contained. It explains what the tool does, the required inputs, and exactly what will be returned. The lack of an output schema is compensated by the explicit Returns section. No critical operational detail is missing for correct usage.

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 coverage is 0%, so the description carries full responsibility for parameter meaning. The Args section explicitly documents all three parameters: principal as an amount in rupees, annual_rate with a concrete example of percentage notation, and tenure_months as loan tenure. This goes well beyond the bare schema, providing units, example, and format that are essential for correct invocation.

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 uses a specific verb and resource: 'Calculate EMI for a loan with year-by-year amortisation schedule.' This clearly distinguishes the tool from siblings like calculate_sip, calculate_cagr, and calculate_fd_maturity by naming the exact financial computation and adding the amortization detail. An agent can immediately understand what this tool does and that it is loan-specific.

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 implies usage for loan EMI calculations but does not explicitly state when to prefer this tool over alternatives or when not to use it. Sibling tools cover other financial calculations (SIP, CAGR, FD), so an agent might infer the right choice from the tool name and description, but no direct routing guidance is provided. This is clear context without exclusions, so it falls at the 'implied usage' level.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.