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

Annotations already declare readOnlyHint=false, so 'Remove' is consistent and no contradiction exists. However, the description adds no behavioral detail beyond the bare action: nothing about idempotency (what happens if a label isn't attached), atomicity (partial failure if one label_id is invalid), or whether the operation affects other case data. For a mutating tool with all-false annotations, this is thin.

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 a single 8-word sentence with the action verb front-loaded and zero filler. It earns high marks for efficiency, though it is arguably so sparse that it sacrifices informative content — a tradeoff reflected in the other dimension scores.

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?

There is no output schema, so the description should convey what the caller gets back (success confirmation, updated case, etc.), but it doesn't. It also fails to clarify queue_id's necessity or failure behavior. For a 3-parameter mutating tool with no annotation or schema support, an agent is left guessing key operational details.

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?

With 67% schema coverage, case_id and queue_id have basic schema descriptions, but the role of queue_id is never explained — it is unclear why a queue identifier is required to unlink case labels. label_ids lacks a property-level description, and the tool description only loosely maps 'the given labels' to label_ids without clarifying relationships or constraints among the parameters.

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 'Remove the given labels from a case' uses a specific verb (remove) and names both the resource (labels) and the scope (a case). It is clearly distinguishable from sibling unlinkClarityProcessLabels by the 'case' qualifier, and from assignCaseLabels by being the inverse operation. It doesn't explicitly name sibling alternatives, but the action and resource are unambiguous.

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?

No guidance is given about when to use this tool versus assignCaseLabels or other label-related tools, and no exclusions or prerequisites are stated. The only signal is the terse action itself, which leaves context selection entirely implicit.

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