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

Annotations already convey idempotentHint=true (safe to retry) and destructiveHint=false (no destruction). The description adds important behavioral context: it consumes AI credits (a cost/resource implication) and implies it processes a batch (max 50). No contradiction with 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?

Two concise, front-loaded sentences. The first sentence states the core function, the second provides critical usage guidance. Every word adds value; no 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 low complexity (1 param, no output schema), the description is sufficient. The agent understands input, behavior (AI credit consumption), and constraints (max 50). A minor gap: the output format (returned labels/priority) is not described, but since there is no output schema, this is a soft miss rather than a hard requirement.

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 coverage is 100% (only one parameter, 'email_ids', well-described with array type, string items, and max 50 limit). The description reinforces that these are emails 'to categorise' and adds the consumption cost context, which helps the agent decide which IDs to pass. No additional parameter documentation is needed beyond what's already provided.

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 uses a specific verb ('Run AI categorisation') and resource ('batch of inbox emails') and states the outcome ('label intent and priority'). This clearly distinguishes it from siblings like 'archive_email', 'reply_to_email', or 'get_email', which handle different operations on emails.

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 advises to only pass emails that need triaging due to AI credit consumption. This provides clear when-to-use guidance. However, it does not explicitly mention when NOT to use this tool (e.g., for already categorized emails) or name specific alternative tools, though the sibling list provides implicit context.

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