add_tea

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

With no annotations provided, the description carries full responsibility and does so thoroughly. It discloses that exact-name matches with built-in teas restore original parameters, that new teas get category-default brewing parameters, that 0/-1 means use defaults, and that batch mode does not support explicit parameters.

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 front-loaded with a concrete usage example, followed by concise behavioral notes and a structured parameter list. Every sentence adds useful information, and the format is easy for an agent to parse.

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's complexity—batch mode, defaults, fuzzy categories, restore behavior—the description covers the crucial operational details well. It does not explain every edge case, such as duplicate non-built-in tea names, but the core invocation path is complete and the output schema exists to cover return values.

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 0%, so the description must fully compensate. It explains name separators, fuzzy category matching with an example, note content examples, and the special semantics of g/temp/minutes/rinse, including batch-mode restrictions. This goes far beyond the bare parameter names in the schema.

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 states a specific verb and resource: adding new tea to inventory, with a natural-language trigger 「我买了XX」. It also clarifies batch addition with examples, which clearly distinguishes this from sibling tools like remove_tea or record.

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 opening examples make the intended invocation context clear: when the user reports buying tea, including batch purchases. It does not explicitly name alternatives or exclusions, but the context is unambiguous enough for an agent to select this tool over siblings.

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