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

Annotations already declare readOnly/idempotent/non-destructive and closed-world, so the safety profile is covered. The description adds beyond that: the result ordering (lowest per-unit price first) and the per-strength/form aggregates (lowest, median, highest), which is real behavioral context. It never mentions the limit cap (max 25) or what happens when no brands match, so a 5 isn't warranted.

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?

Two sentences, no filler, with the result shape front-loaded ahead of the usage examples. The first sentence is long and crams ordering plus three aggregate stats together, which slightly hurts scanability but nothing is wasted.

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?

No output schema exists, and the description handily fills that gap by describing ordering and aggregate values; annotations carry the safety profile. The only material omission for a 3-parameter tool is the limit parameter's role and cap, so an agent may not realize how to control result size.

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?

At 67% schema coverage, molecule and strength are already documented in the schema, and the description's mention of composition and strength/form echoes them. The limit parameter is undocumented in both place and behavior — the description never explains that it caps the number of brands returned. Baseline 3 fits given partial coverage.

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 and resource (every brand of one composition, priced per unit) plus the exact ordering and aggregates returned, which clearly separates it from get_brand (one brand) and search_medicines (lookup). An agent can decide between them without opening any 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?

Concrete trigger phrases ('cheapest <generic>', 'how much should <generic> cost') give a clear context for use. It stops short of naming the sibling tools or stating when-not to use it, so the routing is implied rather than explicit.

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