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

No annotations are provided, so the description must carry the behavioral burden. It discloses that the inbox is created, saved locally, affects other tools, and returns the address. However, it doesn't mention provider failover behavior or any limits on creating multiple inboxes, which would add useful transparency beyond the basic creation side effect.

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 tight sentences with no filler. The core action is front-loaded, and the second sentence provides essential side-effect and return-value context without 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?

For a simple creation tool with optional parameters and no output schema, the description covers the necessary facts: what is created, where it is stored, how it relates to sibling tools, and what the return value is. No critical information for correct invocation 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%, so the parameters are already fully documented in the schema. The description adds no parameter-specific meaning, but it doesn't need to; the baseline of 3 applies because the schema does the heavy lifting.

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 and resource: 'Create a brand new disposable email inbox.' It also clarifies the inbox is saved locally and returns the full email address, which distinguishes it clearly from sibling tools like 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 gives clear context for when to use the tool: before other tools, to obtain an email address for sign-up forms. It doesn't explicitly list exclusions, but the sibling tools are distinct operations (listing, reading, waiting), so the usage context is unambiguous.

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 behavioral disclosure. It adds the useful default-inbox behavior, but does not state whether listing messages has side effects, whether it is read-only, or what happens when no messages exist. This is a partial 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 one clear, front-loaded sentence with no filler. The main action appears first, and the default behavior is included parenthetically without bloating the text.

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 read-style tool with one optional parameter and no output schema, the description covers the basics: what it lists and the default address behavior. However, it does not describe what the returned message list contains (IDs, subjects, etc.), which is relevant given the lack of an output schema. The tool is functional but not fully self-sufficient.

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%, and the single optional 'address' parameter is already described in the schema as 'Inbox address; defaults to the most recent inbox'. The description mostly repeats this same information, adding the 'disposable inbox' framing but no new parameter-level semantics beyond the schema.

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 and resource: 'List the messages currently in a disposable inbox'. It also clarifies the default behavior of using the most recently created inbox. This clearly distinguishes it from sibling tools like read_message, create_inbox, and wait_for_code.

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 no explicit guidance on when to use this tool versus its siblings. It does not mention alternatives such as read_message for a specific message or create_inbox for creating an inbox, so an agent is left to infer the appropriate context.

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. It discloses the read-only nature, the detection of verification codes, the listing of attachment metadata, and the conditional saving behavior with the caveat 'where the provider supports downloads'. This gives the agent a solid behavioral model of the tool's side effects.

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 fluff: the main purpose is front-loaded, and the optional save behavior is stated concisely with the provider-support caveat. Every sentence adds value.

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 read tool with three parameters and no output schema, the description covers what is returned (body, verification code, attachment metadata) and the optional disk-saving behavior. It does not explain error cases or how it relates to wait_for_code, but these are minor gaps given the tool's simplicity.

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 fully documents all three parameters. The description adds some context for save_dir (specifying it also saves the HTML body) and implies id comes from list_messages, but these are incremental beyond the schema. The baseline of 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 a specific verb and resource: 'Read the full body of a message by id'. It also adds distinctive details (verification code detection, attachment metadata) that differentiate it from siblings like list_messages and wait_for_code.

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 implies when to use the tool (to read the full body of a message) and mentions an optional save behavior, but it does not explicitly contrast it with siblings like wait_for_code or list_messages. No when-not-to-use guidance is provided.

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, the description carries the behavioral disclosure burden. It discloses that the tool polls until a message arrives, extracts an OTP, and 'times out gracefully.' This gives useful behavioral context beyond the schema. It does not specify the exact return value on timeout or whether the message is consumed, but the core blocking/waiting behavior is clearly conveyed.

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, no filler. The first sentence states the primary action and result, and the second adds the use context and timeout behavior. Everything earns its place.

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 polling tool with no required parametersable to the schema and no output schema, the description covers the main action, return value, ideal timing, and timeout behavior. Minor gaps remain around what happens on timeout and how this relates to the sibling read/list tools, but nothing an agent needs to invoke it successfully 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%, so all four parameters (from, address, subject, timeout_seconds) are already documented. The description does not add additional parameter-level semantics; it only explains the overall operation. Baseline 3 is appropriate since the schema handles the parameter documentation.

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 ('poll'), a specific resource ('disposable inbox'), and the concrete outcome ('return the verification code (OTP) found in it'). It clearly differentiates this tool from siblings like list_messages and read_message by focusing on waiting for an OTP rather than just retrieving messages.

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 a clear trigger context: 'Ideal right after submitting a sign-up form.' This tells an agent when to use the tool. It does not explicitly name alternative siblings or state when not to use it, so it misses a small opportunity to fully disambiguate from list_messages and read_message.

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