update_cases

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

Annotations indicate a write operation (readOnlyHint=false) and non-destructive (destructiveHint=false), but the description adds little behavioral context. It does not explain failure handling, partial updates, or whether specified fields are overwritten or merged. The detailed fields schema description covers API mechanics but not outcome.

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?

Three sentences with no wasted words: first states action, second states requirement, third states benefit. Front-loaded purpose.

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 mutation tool with no output schema, the description lacks expected details such as return values (e.g., updated case objects or success indicators) and error behavior. The schema descriptions are thorough, but the tool description itself is incomplete for a bulk operation.

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% with thorough descriptions, especially for the 'fields' parameter. The tool description adds a necessary prerequisite hint about 'get_case_fields', which enhances understanding beyond the schema alone.

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 it performs a bulk update on multiple test cases with the same field values, and distinguishes itself from the sibling 'update_case' tool by noting efficiency gains.

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?

It mentions the prerequisite of using 'get_case_fields' for valid field names and contrasts with 'update_case' via efficiency. It implicitly suggests use when updating multiple cases with identical values, but does not explicitly list when to avoid (e.g., different values per case).

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