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

Adds substantial behavior beyond the annotations: the api_key is returned exactly once on the first call with claim_token, must be stored securely, and is used as a Bearer token. This one-time-secret semantics is critical and is consistent with idempotentHint=false, which the description effectively explains.

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?

Four tight sentences with zero filler: purpose and status values first, then the critical one-time key behavior, then polling cadence. Front-loaded and every sentence 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?

No output schema exists, and the description compensates by enumerating all status values and describing what an active status returns. Auth usage and secret handling are covered, so an agent has everything needed to call and act on the 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 coverage is 100%, so the baseline is 3, but the description adds real meaning: claim_token is single-use and its first consumption yields the api_key. session_id semantics are left to the schema, which already documents it as coming from the provisioning tool.

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?

States a specific verb ('Checks') plus the resource ('an account created with provision_account_and_get_payment_link') and enumerates the possible return states (pending_payment, active, expired, suspended). It ties itself directly to the sibling tool that creates the resource, so it is distinguishable from verify_email, search_leads, and the provisioning tool without opening any schema.

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?

Gives concrete operational guidance: poll every 15-30 seconds while pending_payment, and make the claim call once active. It does not explicitly state when to use this versus any alternative or what to do on 'expired'/'suspended', so it falls just short of full when/when-not coverage.

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 cover the safety profile (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true), and the description adds substantial non-derivable detail: the account is created in a pending state, billing is monthly until cancelled, checkout_url must not be opened or paid by the agent, and claim_token must be kept secret. This is exactly the extra context annotations cannot carry.

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 critical usage condition is front-loaded in the first clause, and every sentence is directive rather than filler. It is dense and somewhat long, and it mixes input instructions with output-handling rules, but nothing is redundant with the schema.

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?

With no output schema, the description carries the return-value burden and does so: it names checkout_url, claim_token, and plan.price, and describes the full async flow through check_provisioning_status to the eventual API key. An agent has everything needed to invoke and follow through correctly.

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 all three parameters (agent_id, owner_email, callback_url) are documented in the schema itself. The description references plan.price, checkout_url, and claim_token, but these are outputs rather than inputs, so it adds no input semantics beyond the schema — the baseline 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?

States a specific verb chain and resource: 'Creates a pending Cold Leads account for the human owner's e-mail and returns a Stripe payment link.' It is clearly distinct from the siblings (verify_email, search_leads, check_provisioning_status), which are named or implied by function.

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?

Gives an explicit precondition for use: 'Use only when no working Cold Leads API key is available (other Cold Leads tools return missing_api_key or bad_api_key).' It also states what to do afterward — 'call check_provisioning_status until status is active' — so the agent knows both entry and exit conditions.

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 declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuine non-annotation context: the workspace-only data scope and the fact that it consumes no credits. It stops short of describing result formatting or truncation behavior when limit is hit.

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 the action and data scope front-loaded, followed by the cost/scope caveat. The field enumeration doubles as a return-value summary, so nothing is wasted.

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?

With no output schema, the description usefully lists the returned fields, and it covers the workspace scope and cost model. Minor gaps remain around result ordering and behavior when the limit truncates a large domain's lead set.

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 domain, role and limit are all fully documented in the schema, including domain normalization and the 1–50 limit range. The description adds no parameter-level detail beyond that, which is the expected baseline when 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?

States a specific verb + resource + scope: 'Search the leads already in your Cold Leads CRM for a target company domain,' and enumerates the returned fields. It is clearly distinguishable from the sibling tools (verify_email, provision_account_and_get_payment_link), which are about verification and provisioning rather than retrieval.

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?

Explicitly bounds usage: 'Covers only contacts in your own workspace (Cold Leads has no third-party lead database)' and notes it is free. This tells the agent when NOT to expect results, but it never names an alternative tool or a condition under which a sibling should be used instead.

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 cover safety (readOnly, idempotent, non-destructive), and the description adds substantial behavior beyond that: the conditional SMTP/catch-all logic, the smtp_unreachable reason and null catch_all fallback, the tri-state validity output, the score, the typical latency, and the 1-credit cost. This is exactly the kind of context annotations cannot provide.

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 front-loaded with the checks performed and the return shape, packed into three dense but purposeful sentences. The parenthetical on SMTP fallback is slightly heavy but earns its place by explaining the null catch_all case.

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?

With no output schema, the description appropriately explains the return values (validity, score, reason codes) and the fallback behavior. Cost and latency expectations are also disclosed. An agent has everything needed to decide whether and how to call this 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?

Schema coverage is 100%, so the single parameter is already documented, and the 0-params baseline logic does not strictly apply. The description does not add syntax/format detail beyond the schema, but it enriches understanding by implying what gets evaluated against that input. Baseline 3-4 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 names the specific action (verifies an e-mail address) and enumerates exactly what is checked (syntax, disposable domain, role account, MX records, SMTP mailbox, catch-all). This is a precise verb+resource statement that clearly distinguishes it from the lead-search and provisioning siblings.

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?

Usage context is implied: you call this to validate an address before relying on it. However, the description offers no explicit when-to-use vs alternatives guidance and does not explain how this relates to the sibling tools (e.g. whether to verify before provisioning). Adequate but with a clear gap.

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