customer_detection

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It provides no information about return structure, side effects, authorization requirements, pagination behavior, or error conditions. The term 'query' implies a read operation, but that is minimal and not sufficient for a tool with this complexity.

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 concise, with a single line listing variables and a truncated JSON example. It avoids bloat but is under-specified for a 7-parameter tool. The front-loaded 'Detections · query customerDetection' is a minimal identifier, but the brevity sacrifices necessary context.

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 7-parameter query tool with no output schema and no annotations, the description is incomplete. It fails to describe what the tool returns, how pagination works, or how the filter should be structured beyond a partial example. It also omits any mention of the customer_slug override header that appears in the schema, leaving the agent without critical context.

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?

The schema already provides descriptions for all 7 parameters, but they are non-semantic GraphQL type labels. The description adds a partial example variables object that shows fields like 'activityLogType' and 'bulkJobId', giving some practical insight. However, the example is truncated and does not explain each parameter's purpose, so it adds only marginal value over the schema's baseline.

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 'Detections · query customerDetection,' which essentially restates the tool name without clarifying whether it fetches a single detection or lists them. It does not distinguish itself from sibling tools like 'customer_detections' or 'customer_detection_activity_log_entries'. The presence of required 'id' and 'by' parameters hints at a single-item query, but this is never explicitly stated.

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 offers no guidance on when to use this tool versus alternatives. It merely lists variables and a truncated example, with no mention of use cases, prerequisites, or exclusions. The agent is left to infer the intended usage from the name alone.

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