Email Server

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

No annotations are provided, so the description carries full burden but fails to disclose any behavioral traits such as whether it's read-only, destructive, requires authentication, or has rate limits. It offers no information beyond the basic purpose, leaving the agent without critical operational context.

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 a single, efficient sentence with no wasted words, making it appropriately concise. However, it lacks front-loading of key details, as it only states the basic purpose without elaboration, slightly reducing its effectiveness.

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 simplicity (1 parameter, no output schema, no annotations), the description is incomplete. It fails to provide necessary context such as expected behavior, output format, or usage scenarios, leaving gaps that hinder an AI agent's ability to invoke it correctly despite the straightforward schema.

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 input schema has 100% description coverage, with the 'name' parameter clearly documented. The description does not add any meaning beyond the schema, but since the schema is comprehensive, the baseline score of 3 is appropriate as it adequately covers the parameter without redundancy.

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 'A simple greeting tool' restates the tool name 'greet' in a tautological manner, providing no specific verb or resource details. It does not distinguish from the sibling tool 'send_email', making it vague and minimally informative beyond the obvious.

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?

No guidance is provided on when to use this tool versus the sibling 'send_email' or any other alternatives. The description lacks any context, prerequisites, or exclusions, offering no help for an AI agent in selecting between tools.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the Resend API but doesn't describe authentication requirements, rate limits, error handling, whether emails are sent immediately or queued, or what happens on success/failure. For a mutation tool with significant impact (sending emails), this is a substantial gap in behavioral context.

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 extremely concise (one sentence) with zero wasted words. It's front-loaded with the core purpose. However, it's arguably too brief for a tool with 11 parameters and no annotations, potentially sacrificing completeness for brevity.

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?

For a complex email-sending tool with 11 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what the tool returns, error conditions, authentication requirements, or practical usage patterns. The agent would struggle to use this tool effectively without significant trial and error.

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 documents all 11 parameters thoroughly. The description adds minimal value by mentioning html_content and text_content as content options, but doesn't provide additional semantic context beyond what's in the schema. This meets the baseline for high schema coverage.

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 action ('Send emails') and the target system ('via Resend API'), which provides a specific verb+resource combination. However, it doesn't differentiate from the only sibling tool 'greet', which appears unrelated, so this isn't a distinguishing factor. The description could be more specific about what kind of email sending this enables.

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 minimal guidance about content options ('Provide html_content and/or text_content') but offers no context about when to use this tool versus alternatives, prerequisites, or typical use cases. There's no mention of when not to use it or what alternatives might exist for email sending.

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