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

Annotations already declare this as read-only/idempotent, and the description adds useful behavioral context: database scope, curation, available filters, and what results contain (tasting profiles, brew methods, buy links). It does not mention result ordering or pagination behavior, but those are minor for a search tool.

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 compact sentences: the first establishes scope, the second covers filters and returns. No filler, redundant qualifiers, or boilerplate; the key information is front-loaded.

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 search tool with seven optional parameters, all documented in the schema, the description supplies the missing context: result contents, currency for price filters, and the catalogue's curated nature. No output schema is provided, but the returns are described well enough for correct invocation.

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%, so the schema already documents every parameter and even the enum values. The description repeats the main filters but adds little semantic detail beyond the schema; this is the baseline 3 rather than a higher score.

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 names a specific verb ('Search'), a bounded resource ('1,100+ curated specialty coffees in the Percolate database'), and the main filter dimensions. This clearly distinguishes a catalogue lookup from siblings like get_coffee, compare_coffees, or trending_coffees.

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?

It gives clear context: use this when you need to find coffees by text, category, roast, brew method, or price. It does not explicitly state when to prefer a sibling such as get_coffee for a known coffee ID or compare_coffees for side-by-side comparison, so it stops short of a 5.

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