bind_email

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

The description discloses the mutation behavior (binding email) and explains consequences: key becomes recoverable, receipts are routed, and email usage is limited to transactional purposes unless opt-in. It also states the key continues to work if binding fails, which is beyond the annotations (readOnlyHint=false, destructiveHint=false). 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?

The description is relatively long but well-structured with front-loaded purpose and clear delineation of parameters, consent, and return value. It earns its length by covering important behavioral and consent details, though it could be slightly more concise.

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 has 3 parameters, no output schema, and minimal annotations, the description thoroughly covers behavior, parameter roles, consent requirements, and what is returned ('unlocked benefits + confirmation'). It provides sufficient context for the AI agent to decide when and how to invoke the tool.

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 description adds valuable meaning for all three parameters (email, api_key, marketing_opt_in) beyond the schema, which has 0% coverage. However, it incorrectly labels 'email' as required while the schema has no required properties, causing a potential contradiction that may confuse the AI agent. This reduces reliability.

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 tool's purpose: 'Tie your DC Hub key to your human's email so the key is RECOVERABLE and upgrade receipts land in the right inbox.' It uses a specific verb and resource, and distinguishes itself from siblings by noting it's optional and unrelated to other tools.

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 says when to call the tool ('once your human shares their email'), that it's optional and the key works without it, and provides guidance for the marketing opt-in parameter. It includes fallback behavior if the email is not accepted, giving clear context for use.

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