bulk_remove_labels

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

With no annotations, the description must fully disclose behavior. It only states the basic operation and parameter formats, but omits side effects, idempotency, error handling, or whether partial failures occur. For a bulk mutation tool, this is insufficient.

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 extremely concise (two sentences plus a parameter list) with front-loaded purpose. Every word serves a function, and there is no redundancy or unnecessary information.

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?

While the description explains purpose and parameters adequately for a simple tool, it lacks details about the output, error conditions, or behavior in edge cases. Given that an output schema exists, completeness is adequate but not rich.

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 0%, but the description adds value by explaining that 'email_ids' are 'Comma-separated email IDs (max 50)' and 'mailbox_ids' are 'Comma-separated mailbox IDs to remove.' This clarifies the format and batch limit beyond the schema's plain string type.

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 'Remove mailbox labels from multiple emails,' specifying the verb (remove), resource (mailbox labels), and scope (multiple emails). It distinguishes this tool from siblings like 'add_labels' and 'bulk_add_labels' by indicating a removal operation.

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 provided on when to use this tool versus alternatives. Given sibling tools like 'remove_labels' (likely for single emails) and 'bulk_add_labels', the absence of usage context leaves the AI uncertain about selection criteria.

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