get_diagnostics

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

The annotation readOnlyHint=true already communicates that this is a safe read operation. The description adds meaningful behavioral context by warning that all diagnoses are hypotheses, not facts, which is important for correct interpretation of results. There is no contradiction between the description and annotations.

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 two short sentences with no filler. The main action is front-loaded, the data source is provided, and the important caveat about hypothesis status is placed at the end without bloating the description.

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 simple read-only tool with a single well-documented parameter and an output schema, the description is complete. It conveys the purpose, data source, and a critical interpretive caveat, leaving no major gap that would prevent an agent from invoking 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 description coverage is 100%, with operator_id fully documented as a pseudonymous operator ID. The description itself does not add much parameter-level meaning, but the schema already carries the necessary semantics, so the baseline score of 3 is appropriate.

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: getting operator diagnostics, and it explains the source of those diagnostics (divergence analysis). It is clear what the tool does, though it does not explicitly distinguish it from related sibling tools like find_usage_operation_divergence.

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 gives no guidance on when to use this tool versus alternatives such as find_usage_operation_divergence or get_data_quality. The context of "divergence analysis" provides only a weak implication of intended use, with no explicit exclusions or selection criteria.

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