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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the core safety profile is covered. The description adds 'no data is stored' which is a small privacy note beyond the annotations, but it doesn't disclose any other behavioral traits (e.g., rate limits, error behavior, or response format nuances). It is consistent with annotations, but adds limited extra value.

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 a single, information-dense sentence. It front-loads the action and resource, provides examples, enumerates return fields, and includes the read-only note—all without any filler or redundancy. Every clause earns its place.

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 the tool has only one input, no output schema, and strong annotations, the description does well: it states exact return fields and the GoDavaii page, and notes read-only behavior. The only gaps are edge-case handling (e.g., not-found medicine, loose brand matching) and whether the output is structured vs. prose, but these are minor for a simple lookup tool.

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 100% because the input `name` has a description ('Brand or product name as sold in India'), fulfilling the baseline of 3. The description adds concrete examples (Dolo 650, Crocin, Augmentin 625) and the 'Indian medicine' context, which helps an agent pick valid values beyond the schema's generic description.

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 ('look up') and resource ('Indian medicine by brand or product name'), lists the exact fields returned (composition, category, company, reference price, GoDavaii page with uses/side effects/alternatives), and gives concrete examples. This clearly distinguishes it from siblings like ask_health_ai (general Q&A) and check_drug_interaction (interaction checking).

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: if you need Indian medicine brand/product facts, use this tool. However, it never explicitly contrasts with ask_health_ai or check_drug_interaction, nor says when not to use it. The context makes the intended use reasonably clear, but there is no explicit routing or exclusion.

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