Apps Script MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the core behavior (adding/removing labels) and provides practical examples, but lacks details on permissions, error handling, or side effects (e.g., what happens if conflicting labels are added/removed). It doesn't contradict annotations, but could be more comprehensive given the mutation nature of the tool.

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 well-structured and front-loaded with the core purpose, followed by helpful reference information (common label IDs), parameter details, and practical examples. Every section earns its place by providing essential guidance without redundancy, making it efficient and easy to scan.

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 complexity (mutation with 4 parameters), no annotations, and an output schema (which reduces need to describe return values), the description is quite complete. It covers purpose, parameters with semantics, and usage examples. A minor gap is the lack of explicit behavioral constraints (e.g., rate limits, auth requirements), but overall it provides strong contextual 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?

The schema description coverage is 0%, so the description must fully compensate. It does so excellently by listing all 4 parameters with clear explanations, common label IDs with descriptions, and practical examples showing how to use 'add_labels' and 'remove_labels'. This adds significant meaning beyond the bare schema, making parameter usage intuitive.

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 ('Modify labels') on a specific resource ('Gmail message'), distinguishing it from sibling tools like 'get_gmail_message_tool' or 'search_gmail_messages_tool'. It uses precise language that immediately communicates the tool's function without ambiguity.

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 provides clear context for when to use this tool through examples (e.g., 'Archive: remove_labels=["INBOX"]', 'Mark read: remove_labels=["UNREAD"]'), which implicitly guides usage. However, it doesn't explicitly state when NOT to use it or mention alternatives among siblings, though the examples cover common scenarios.

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