calculate_ppf_maturity

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds useful behavioral context beyond that: it notes the EEE tax treatment, fact that returns come in a standard envelope, and that the interest rate is government-administered and revised quarterly. No contradiction with annotations exists.

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, highly structured, and every section earns its place: purpose, use cases, arguments, return, and notes. The information is front-loaded with the core action and use case before detailed parameter/return details. There is no fluff or redundant filler.

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?

Given a rich input schema, output schema, and annotations, the description covers all necessary decision-making signals: when to use it, key constraints, what it returns, and important tax/rate context. It is sufficiently complete for the agent to invoke the tool correctly without missing critical context.

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 is good, but the description adds meaningful value by specifying constraints not fully in the schema: annual_investment is capped at ₹1,50,000, tenure_years should be one of 15/20/25/30, and the default interest rate is explicitly tied to FY2025-26. This goes beyond the schema descriptions and provides practical limits.

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 opens with a specific verb and resource: 'Calculate PPF maturity amount with year-by-year breakdown.' This clearly identifies what the tool does and differentiates it by the maturation product and the breakdown style, distinguishing it from sibling calculators like FD or RD maturity.

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 gives explicit use contexts: 'when planning long-term savings, comparing investment options, or calculating retirement corpus.' It does not explicitly say when NOT to use this tool or mention sibling alternatives, but the stated scenarios are clear enough for an agent to select this tool confidently.

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