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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description only needs to add contextual behavior. It adds that the balance is scoped to the configured API key and counts hosted checks, but says nothing about response shape or failure cases.

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?

A single sentence that front-loads the core function and contains no redundant filler. It is concise without sacrificing the key detail about API-key scoping.

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 parameterless, read-only balance check, the description gives enough to know when and why to call it, and annotations cover the safety profile. It does not describe the exact return representation, but the 'how many' wording strongly implies a numeric count.

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?

There are zero parameters, so no parameter documentation is required. The description usefully clarifies that the API key is configured externally rather than passed as input, supporting the no-parameter design.

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 names a specific resource (remaining hosted checks) and scope (configured API key), and the interrogative form clearly signals a read-only quota query. This distinguishes it from siblings such as buy_credits and verify_email.

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?

There is no explicit 'use when' statement or mention of alternatives; the intended context (checking remaining quota) must be inferred from the resource type and sibling tools. The usage context is implied rather than directly stated.

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?

Annotations mark readOnlyHint=false (write operation) and openWorldHint=true (external effects). The description discloses the external Stripe payment flow and the delayed credit delivery upon confirmation, which adds valuable context beyond the annotations. It does not cover failure scenarios or refunds, but it adequately explains the primary 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 concise sentences, no fluff. The action is stated first, followed by the commercial details and the payment-confirmation flow. Every clause contributes to the agent's understanding of how to invoke the tool and what to expect.

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 tool with no output schema and annotations covering safety, the description is nearly complete. It explains the action, pricing, and the confirmation mechanism. It stops short of explicitly stating the return value (the checkout URL) and handling failures, but these are minor gaps given the 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?

The single parameter 'packs' is fully described in the schema (coverage 100%), with default and range. The description adds the cost per pack ($9 per 10,000) and clarifies that a payment is one-time and credits never expire, giving the agent useful pricing context to help with user requests. This exceeds 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 states a specific action ('Get a Stripe Checkout link'), the resource (hosted checks credits), and even key commercial terms. It is clearly distinct from siblings like signup, verify_email, verify_batch, and balance, which deal with identity and account state rather than purchasing.

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 implicitly communicates when to use this tool: when the user needs more hosted-check credits. It doesn't explicitly contrast with alternatives, but the tool's purpose is self-evident given sibling names, and the description includes the cost per pack and the payment flow, which clarifies its role.

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 real behavioral details beyond the annotations: it creates a key, saves it locally, emails the key, includes a 100-free-check quota, and enforces one key per address. This gives an agent a strong sense of side effects and constraints. 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 three short sentences, front-loaded with the primary return value. Each sentence adds a distinct useful detail: returns a key, saves it locally, and the one-per-address constraint.

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 single-parameter tool with no output schema, the description covers the return value, side effects, quota, and a uniqueness constraint. Nothing critical is missing for an agent to correctly invoke it.

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 baseline is 3. The description adds a bit of context by noting the key is mailed to the given address, but it does not meaningfully extend the schema's explanation of the email parameter.

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 clear verb ('Sign up'), the resource (email address), and the outcome (returns an API key with 100 free checks). It also explains that the key is saved locally, which distinguishes it from the sibling verification and billing 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 clearly implies this is the setup step for the other tools: 'saves it locally for the other tools' tells an agent when this should be used. It does not explicitly say when not to use it or name alternatives, but the context is clear enough.

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 adds substantial behavior beyond the annotations: it explains the send/hold/kill action taxonomy, the difference between DNS-tier and hosted-tier behavior, and the credit cost model. This is exactly the contextual information an agent needs to predict side effects and constraints.

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 compact and front-loaded with the key capacity limit, followed by the result shape and action meanings, then cost mechanics. Every sentence earns its place with no repetition 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?

Given no output schema, the description still covers the result shape, each action value, tier behavior, and cost implications. This is enough for an agent to select and call the tool correctly without additional lookup.

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 baseline is 3. The description adds meaning by explaining what hosted probing entails, how free tier skips checks.smtp, and that max 500 addresses applies per call, enriching the semantic understanding beyond the raw 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 uses a specific verb and resource: 'Check up to 500 addresses in one call.' It clearly positions this as the batch variant of email verification, distinguishing it from the single-address sibling verify_email by the batch size and result format.

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 clearly communicates batch use with a 500-address limit, giving the agent context for when this tool is appropriate. It does not explicitly name verify_email or state when not to use it, so it falls just short of fully explicit alternative routing.

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?

Annotations already mark this as read-only, idempotent, and non-destructive. The description goes beyond annotations by detailing the result shape, the meaning of each action value, the behavior of checks.smtp across tiers, and the credit cost of the hosted SMTP probe. This gives the agent a rich understanding of side effects and tier-dependent behavior.

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 dense but every sentence earns its place: core purpose, result format, action semantics, tier behavior, and credit cost are all covered. It is front-loaded with the primary use case and flows logically into operational details without fluff.

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?

Despite having no output schema, the description fully documents the return shape and the meaning of each action. It also covers tier selection, credit cost, and default behavior. An agent has everything needed to call the tool correctly and interpret its result.

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 both parameters. The description adds meaningful context for the 'hosted' parameter by explaining when the hosted SMTP probe is used, when the free DNS tier is used, and that it costs 1 credit. This is useful information beyond the schema's simple boolean description.

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: 'Check whether an email address can receive mail before sending to it.' It clearly identifies the tool's purpose and differentiates it from siblings like verify_batch by focusing on a single email address and providing a concrete decision outcome (send/hold/kill).

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 sending to it') and explains the hosted versus free DNS tier behavior. It does not explicitly name alternatives or state when not to use it, but the singular-versus-batch distinction with verify_batch is strongly implied.

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