find_customer

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

With no annotations provided, the description carries full burden and delivers complete behavioral details: ID vs email lookup behavior, case-insensitive search, complete object return including loyalty summary, and error conditions. No contradictions.

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 well-structured with sections for lookup behavior, parameters, validation, examples, returns, and raises. It is front-loaded with the main purpose. Slightly verbose but every section adds value. Could be slightly more concise.

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 simple task of finding a customer with two parameters, and an output schema present, the description fully covers the input requirements, validation, return data structure, and error handling. No gaps.

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 0% as the schema only provides type and default. The description compensates thoroughly by specifying exact validation rules (email format, id prefix cust_), requiring exactly one parameter, and providing examples. This adds significant meaning beyond 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 clearly states the verb 'Find' and resource 'customer', with explicit lookup methods by email or ID. It distinguishes itself from sibling tools like get_campaign and list_products by focusing on customer retrieval.

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 provides clear context on when to use the tool, including validation rules that exactly one parameter must be provided and format requirements. It implicitly indicates not to use when data is not a customer, but lacks explicit when-not or alternative tool references.

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