modify_gmail_message_labels

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 states the tool modifies labels (implying mutation) but lacks critical details: required permissions (e.g., Gmail API scope), whether changes are reversible, error handling (e.g., invalid label IDs), or rate limits. The return value is mentioned but not elaborated (e.g., success/failure details).

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: the first sentence states the core purpose, followed by a clear 'Args' and 'Returns' section. Every sentence adds value—no redundancy or fluff. It efficiently communicates essential information in a compact format.

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 (mutation with 5 parameters), no annotations, and no output schema, the description is partially complete. It covers purpose and parameters well but lacks behavioral context (permissions, errors) and detailed output explanation. For a mutation tool, this leaves gaps that could hinder correct agent invocation.

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%, so the description must compensate. It explicitly documents all 5 parameters with names, types, and brief semantics (e.g., 'user_google_email: The user's Google email address. Required.'). However, it doesn't explain the 'service' parameter (present in schema but missing from description), leaving one parameter undocumented. The coverage is high but incomplete.

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 ('Adds or removes labels') on a specific resource ('from a Gmail message'), distinguishing it from sibling tools like 'manage_gmail_label' (which likely manages label definitions) or 'get_gmail_message_content' (which reads content). The verb+resource combination is precise and 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing valid label IDs from 'list_gmail_labels'), when to prefer it over other tools, or any constraints (e.g., cannot add and remove the same label simultaneously). Usage context is implied but not explicit.

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