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

Annotations already establish the operation is read-only and non-destructive. The description adds meaningful behavioral context: results are limited to top 5, the cashback/rewards value is estimated, annual income is used as an eligibility filter, and prefer_no_annual_fee changes prioritisation. No contradictions with annotations are present.

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 structured with a one-sentence summary followed by peer Arg/Returns lines. Every line adds information, and no unnecessary boilerplate or repetition is present.

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?

The tool is simple, annotations confirm safety, and the description covers inputs and the high-level return shape despite lacking an output schema. It could be slightly more precise about the exact fields inside each returned card and whether all monetary amounts are INR, but nothing critical is missing for calling it correctly.

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?

With 0% schema description coverage, this description carries the entire burden for parameters and succeeds. It defines monthly_spend with units (rupees), enumerates all valid primary_category values, explains annual_income as an optional eligibility filter, and specifies that prefer_no_annual_fee prioritises lifetime-free cards.

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 opening sentence uses a specific verb ('Recommend') and a precise resource ('Indian credit cards'), and adds the basis ('spending pattern'). It also states the output ('Top 5 cards with estimated annual cashback/rewards value'), which clearly separates it from sibling tools like compare_products or find_best_fd.

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 the use case — when a user wants Indian credit-card recommendations based on monthly spend and category — but it never explicitly states when to prefer this tool over siblings such as compare_products or get_product_details, nor gives exclusion conditions. Context is present but alternatives are not named.

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