draft_customer_detection

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only signals 'query', which hints at a read-only operation, but it does not state read-only behavior, pagination, authorization requirements, or any side effects. The truncated example variable block adds no explicit transparency about behavior.

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 relatively short, but it includes a truncated raw JSON example that is not clearly formatted and cuts off mid-string. It front-loads the operation name and variable list, but the abrupt example makes it feel unstructured and less polished.

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?

This is a 6-parameter query with no output schema, and the description does not explain what data is returned, how filtering works, or the meaning of 'by'. The example is truncated and incomplete. Given the complexity and missing schema information, the description is insufficient for an agent to confidently select and invoke the tool correctly.

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 all parameter names and GraphQL types. The description adds an example filter object with fields like activityLogType, bulkJobId, and draftCustomerDetectionId, which gives some insight into the expected shape. However, it does not explain the meaning or purpose of each parameter, and the required 'by' parameter remains opaque.

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 is essentially a restatement of the tool name: 'query draftCustomerDetection'. It adds 'Detections ·' as a category but does not say in plain language what this query returns or what action it performs. It is not a specific verb like 'list' or 'retrieve', and it does not meaningfully distinguish from sibling detection tools beyond the 'draft' qualifier.

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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusion criteria. The description only lists variables and an example payload, which implies usage mechanics but does not explain the intended use case or context.

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