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

With no annotations provided, the description carries the burden of disclosing behavior. It discloses that the tool creates a mailbox, returns an address and id, and randomizes both name and domain when invoked without arguments. It does not mention lifecycle details like expiry, but the core side effect and return contract are transparent.

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 sentences convey purpose, return value, default behavior, and integration with sibling tools. The most important information is front-loaded, and every sentence earns its place with no redundant filler.

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?

The tool is simple with one optional parameter and no output schema, so the description's explanation of returned values ('address to paste into a signup form' and 'id used by the other tools') is enough for an agent to invoke it correctly and use its result. Nothing essential is missing.

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%, so the schema already documents localPart well. The description adds value by stating that the domain is also random when no arguments are given, and by signaling that omitted arguments are the recommended default, not just a fallback.

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 states a specific verb, resource, and outcome: 'Create a temporary email address.' It also clarifies the returned artifacts (address and id) and distinguishes the tool from its siblings, which all consume or manage mailboxes rather than create them.

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 gives clear guidance on the common default usage: 'Without arguments you get a random name on a random domain, which is what you usually want.' It does not explicitly name sibling alternatives or state exclusions, but the create-vs-consume distinction makes the intended use clear.

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 the full burden of behavioral disclosure. It clearly warns that the operation deletes the mailbox and everything in it, and it mentions the quota effect. It does not discuss irreversibility explicitly, but 'delete everything' strongly implies permanent destruction.

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 concise sentence that front-loads the action and scope, then adds relevant usage context. Every phrase earns its place with no redundancy or filler.

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 simple one-parameter destructive tool with no output schema, the description covers what it does, what it destroys, when to use it, and why it is optional. Nothing an agent needs to decide whether to call it is missing.

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%, and the schema already explains that mailboxId is 'Mailbox id from create_mailbox'. The description adds no parameter-specific meaning beyond that, so the baseline of 3 applies.

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 states a specific verb ('Delete'), the resource ('the mailbox'), and the full scope ('and everything in it'). This clearly distinguishes it from sibling tools like create_mailbox, wait_for_code, list_messages, and read_message.

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 use it ('once you are done'), and provides the alternative of doing nothing because mailboxes expire in 24 hours. It also gives a reason to use it anyway ('polite and it frees your quota'), making the decision context clear.

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?

No annotations are provided, so the description carries the full burden of disclosing side effects, permissions, or read-only nature. The description only implies a read-only list operation but does not explicitly state that it has no side effects or whether it requires special permissions. This lack of transparency is a significant gap.

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 concise, consisting of two sentences that front-load the primary action and then provide usage context. There is no unnecessary verbosity or repetition.

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?

The description gives a clear trigger scenario for use and describes the output format at a high level (newest first, short previews). It does not detail error conditions or pagination, but for a simple list tool this is acceptable and does not impede correct usage.

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 sole parameter 'mailboxId' is described as 'Mailbox id from create_mailbox', which provides cross-tool context and clarifies the expected value. The schema coverage is 100% for the single parameter, and the description adds meaningful information beyond the type.

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: listing messages in a mailbox, with explicit details about ordering ('newest first') and content ('short preview of each'). It also provides a concrete use case ('when the code extraction found nothing'), making the purpose 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 gives explicit guidance on when to use the tool ('Use it when the code extraction found nothing and you need to look at the mail yourself'), which is helpful. However, it does not explicitly mention when not to use it or contrast it with sibling tools like read_message, but the context is sufficient for most scenarios.

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 the burden of explaining behavior. It discloses that plain text is returned where available, but it does not describe edge cases, error behavior, or whether HTML is ever included.

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 two tight sentences with no filler. The core behavior is front-loaded, followed by a directly relevant usage condition.

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 simple one-parameter read tool, the description covers the action, the return style, and typical usage. No output schema exists, so the return behavior described is sufficient, though error handling and response format could be more explicit.

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 single required parameter is fully documented in the schema: 'Message id from list_messages or wait_for_code'. The description adds no parameter-specific information beyond the schema, so baseline 3 is appropriate.

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 returns the full body of one message and mentions plain text availability. It distinguishes from preview-oriented listing, though it does not explicitly name sibling 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?

"Use it when the preview is not enough" gives clear context for when this tool is appropriate versus lighter alternatives. It does not explicitly name those alternatives, but the guidance is actionable.

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?

The description discloses meaningful blocking behavior: 'It blocks until the message lands, so there is no need to poll or to sleep between calls.' It also states the extracted outputs. However, it does not disclose timeout behavior, what happens if no matching email arrives, or any side effects on the mailbox message.

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 sentences with no wasted words. The main action and result are front-loaded, followed by usage timing and a behavioral note that eliminates unnecessary polling patterns.

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?

The description covers when to call, what it returns, and the blocking behavior, which is sufficient for basic use. With no output schema, it appropriately mentions the return content. It does not cover timeout/error outcomes or how the 'from' and 'since' filters interact, but these are secondary.

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 fully documents all four parameters. The description adds some context around the wait behavior but does not add parameter-specific meaning beyond what the schema already provides, matching the baseline.

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 verb 'wait' and resource 'email', and specifies the exact outputs: confirmation code and activation link. It is distinct from sibling tools like list_messages or read_message because it implies extraction rather than raw message retrieval, but it does not explicitly name or contrast any sibling.

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 gives explicit timing guidance: 'Call this right after triggering the signup.' It also advises against polling or sleeping between calls, which implies when not to use manual alternatives. However, it does not explicitly mention when to choose list_messages or read_message instead.

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