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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds valuable behavioral context: it returns the top 5 FDs sorted by net-of-tax maturity, each showing gross and net amount. This output behavior goes beyond the annotations, though it doesn't discuss data freshness or rate limits.

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 front-loaded with the core purpose, then structured into Args and Returns sections. It is appropriately sized with no redundant sentences; each line adds necessary information, especially given the zero schema description coverage.

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 tool with no output schema and 0% schema description coverage, the description is fairly complete: it documents all parameters, the ranking method, and the return format. It lacks context about the underlying FD data source (e.g., whether rates are current or which providers are included), but this is a minor gap given the closed-world annotation.

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 description coverage is 0%, so the description must carry the full burden, and it does. It defines each parameter: amount (in rupees), years (tenure, with example 1.5 for 18 months), is_senior_citizen (uses senior-citizen rates, typically +0.5%), and tax_slab_pct (income tax slab as 5/10/20/30, noting FD interest is fully taxable and used for net-yield ranking). This adds clear meaning beyond the bare schema titles.

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?

States a specific verb (Rank) and resource (Indian Fixed Deposits) with the ranking criterion (net-of-tax yield) and required inputs (amount + tenure). This clearly distinguishes it from sibling tools like calculate_fd_maturity, which computes maturity for a given FD, without needing to open either schema.

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 explains what the tool does but gives no explicit guidance on when to use it versus alternatives such as calculate_fd_maturity or compare_products. There are no when-not conditions or named alternatives, leaving usage context to inference.

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