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

Annotations indicate readOnlyHint=false and destructiveHint=false, but the description adds valuable behavioral context beyond this: it explains the side effects of removing specific labels (e.g., removing INBOX archives the message, removing UNREAD marks it as read). This clarifies non-obvious consequences not covered by 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 front-loaded with the core purpose in the first sentence, followed by two concise, actionable sentences that provide essential usage notes and behavioral insights. Every sentence adds clear value without redundancy.

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?

Given the tool's moderate complexity, 100% schema coverage, annotations covering safety, and the presence of an output schema, the description is complete. It covers purpose, prerequisites, and key behavioral nuances, leaving no critical gaps for agent understanding.

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%, so the schema already fully documents both parameters (emailId and labelIds). The description adds minimal semantic value beyond the schema, such as referencing list_labels for label IDs and providing example label values, but does not significantly enhance parameter understanding.

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 the specific action ('Remove one or more labels') and target resource ('from an email message'), distinguishing it from sibling tools like add_labels (which adds labels) and list_labels (which lists labels). It provides precise operational context.

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 explicitly references list_labels as a prerequisite to find label IDs, providing clear context for when to use this tool. However, it does not specify when NOT to use it or explicitly contrast with alternatives like add_labels, which slightly limits guidance.

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