Get coffee details

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

Annotations already declare the tool read-only, idempotent, and non-destructive, so no side-effect disclosure is needed. The description adds useful context by spelling out what the returned record contains, which helps set expectations because there is no output schema.

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 focused sentences with no filler; the main purpose is front-loaded and the parameter behavior is stated compactly. The content list is long but each item earns its place in telling an agent what to expect.

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 one-parameter, read-only lookup tool, the description is largely sufficient: it names the lookup modes and previews the output fields despite there being no output schema. It does not address ambiguous-name behavior or error cases, but those are not major gaps for this low-complexity 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 description coverage is 100%, so the schema already explains id_or_name as a coffee id or a name with an example. The description mostly repeats this information, adding only the 'Percolate' identifier context, which is minor.

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: it returns 'Detailed record for one coffee' rather than a list or comparison. The inventory of content fields makes the scope clear and helps distinguish it from broader siblings like search_coffees or compare_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?

Clearly implies when this is appropriate: when an agent needs a single coffee's full record and already has an id or name. It does not explicitly name alternative tools or excluded conditions, but the singular-scope phrasing gives solid context.

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