Black Label Bots Website MCP

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

Annotations already indicate readOnlyHint=false and idempotentHint=false, so the agent knows it's a mutating operation. The description adds the key behavior that it does not charge anything, and returns a continue_url for payment. This provides useful context beyond the 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?

Two sentences with no fluff. The first sentence states the action and the second explains the return and the no-charge behavior. Information is front-loaded and every word 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?

The description covers the core return value and clarifies it does not charge, but it omits details on offer_id choices and quantity semantics. Given the enum of offers and the quantity parameter, an agent may not know which offer to select or what quantity means. The description is adequate for the basic flow but incomplete for correct parameter selection.

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 0%, so the description must compensate for parameter semantics. The description mentions 'one offer' which implies offer_id selects the offer, but it does not explain the enum values or the quantity parameter. The agent is left without guidance on how to choose offer_id or interpret quantity, a significant gap given the enum has many options.

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: 'Start a purchase of one offer' and specifies the resource (offer) and the return (continue_url). It also clarifies that it does not charge anything, distinguishing it from any charging operation. This is a specific verb+resource with clear scope.

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 usage when initiating a purchase, but it does not explicitly state when to use this tool versus alternatives like get_checkout or list_products. No exclusions or alternative conditions are provided. The context of starting a purchase is clear, but the routing to siblings is left to inference.

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 cover readOnlyHint, idempotentHint, and non-destructiveness. The description adds the precondition that the checkout must have been started by create_checkout, but does not disclose response contents or error behavior, which is acceptable given the strong annotation coverage.

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, front-loaded sentence communicates both the action and the required precondition with no filler. Every word serves a purpose.

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 operation with one obvious identifier parameter and rich annotations, the description is sufficiently complete. It could mention the return shape, but the title already indicates status and no output schema is present.

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?

With only one parameter, checkout_id, the schema name is self-explanatory and the description confirms it identifies the checkout to read. However, schema description coverage is 0%, and the description itself adds no parameter-level detail, so it only earns average credit.

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 action ('Read'), a resource ('checkout'), and explicitly ties the tool to create_checkout, distinguishing it from the creating sibling. The title reinforces that it reads checkout status.

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 the tool is used after create_checkout has started a checkout. It doesn't explicitly name alternatives or exclusions, but the relationship to its creator sibling provides sufficient context for appropriate selection.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds context about the content (Stripe-verified prices, billing terms, delivery, live availability), which is useful but does not disclose response format or any edge cases. Since annotations carry the safety burden, this is acceptable.

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, front-loaded sentence that efficiently communicates the tool's purpose and key content. Every word adds value, and the most important information ('Everything an agent can buy') appears first. No fluff or 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 zero-parameter, read-only list tool with no output schema, the description provides sufficient context: it names the entity (products), the source (Black Label Bots), and the included attributes (prices, billing, delivery, availability). It doesn't specify the response format, but that's not critical for such a simple tool. Slightly more detail on how results are structured would push it to 5.

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 tool has zero parameters and the schema is an empty object with 100% coverage. The description correctly omits parameter details because none exist. Per the baseline for 0 parameters, a score of 4 is appropriate; the description doesn't need to compensate for schema gaps.

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 what the tool returns: everything an agent can buy from Black Label Bots, with specific attributes like Stripe-verified prices, billing terms, delivery, and availability. The verb 'list' is implied by 'Everything an agent can buy', which is a specific resource. It distinguishes from siblings like create_checkout and list_services, though it doesn't explicitly name 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 implies when to use this tool (to see available products) but does not explicitly state when not to use it or mention alternatives. Siblings like list_services exist, but no routing guidance is provided. Context is clear but exclusions are absent.

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 cover read-only, idempotent, and non-destructive behavior. The description adds a meaningful behavioral note—'Free; does not request payment'—which is not present in annotations and provides useful context for an agent deciding whether to call this tool. 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 two short sentences, front-loading the core purpose before the payment note. Every word earns its place; there is 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, no-parameter read-only listing, the description sufficiently conveys what the tool returns (service prices, availability, payment requirements). Although no output schema exists, the description gives enough content for an agent to understand the tool's result without needing explicit return-shape details.

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 tool has zero parameters and 100% schema coverage, so the baseline is 4. The description correctly omits parameter details since none exist; there is nothing to add 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 uses a specific verb ('Read') and resource ('website service prices, availability and payment requirements'), clearly distinguishing it from sibling tools like list_products and create_checkout. The scope is explicit and immediately comprehensible.

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 states what the tool reads, which implies when it should be used, but it does not explicitly contrast it with alternatives such as list_products or get_checkout. There is no explicit 'when to use' or 'when not to use' guidance, leaving the context implied rather than 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 already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the description does not need to restate safety. It adds genuinely useful behavioral context: the content is returned as Cloudflare Markdown for Agents or stripped text and is capped at 40,000 characters. It does not say what happens past the cap, which is a minor gap, but it does not contradict the 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?

One sentence with no filler: it front-loads the core action, then adds the domain scope, output format, and character limit. Every clause contributes meaningful information.

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 one-parameter, read-only tool with strong annotations, the description covers the essential operational details: domain scope, output format, and length limit. The main missing piece is explicit guidance on what happens beyond 40,000 characters and how the format choice is made, but overall it is sufficient for an agent to select and call the 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 description coverage is 0%, so the description must compensate for the undocumented url parameter. It does help by constraining the URL to a single https://blacklabelbots.com page, but it does not explain URL normalization, the apparent format choice, or length-cap behavior. Compensation is partial, not complete.

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 the specific action (read), the exact resource type (one blacklabelbots.com page), and the output form (Markdown or stripped text, up to 40,000 characters). This clearly distinguishes it from siblings like search_pages and site_info without needing to open their schemas.

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 it should be used when full page content is needed, and the 40,000-character cap suggests a scope, but it never explicitly says when to prefer this over search_pages or site_info, nor does it name alternatives or exclusions. Usage context is implied rather than 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?

Adds substantial context beyond the annotations: the service is paid via a public x402 endpoint, an unsigned call is free and returns payment requirements, the wallet-signing step requires operator authorization, private keys must never be sent, and an uncertain response should not trigger a fresh payment. This retry guidance is especially valuable given idempotentHint=false. 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?

Five dense sentences cover purpose, payment model, quote behavior, authorization flow, security, and retry/idempotency guidance with zero filler. The core purpose is front-loaded before the payment mechanics.

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 tool with no output schema, the payment/retry flow is exceptionally well covered. The main gap is that the actual audit result is never described, and the format of the 'payment requirements' response is unspecified. Still, the trickiest parts of this unusual monetized tool are fully handled.

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 baseline is 3, but the description adds real meaning: it explains the payment_signature lifecycle (omit = free quote, provide = paid execution), clarifies that url must stay stable across the two-phase flow, and warns against sending a private key as the signature. This goes beyond the schema's one-line field descriptions.

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 verb+resource clearly: running an 'AI search readiness audit.' The paid x402 endpoint and the 'read list_services for the current price' pointer subtly differentiate it from the free sibling tools, but it never explicitly contrasts with the other run_* audit tools (run_llms_txt_draft, run_structured_data_pack), so an agent must infer the boundary.

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 an explicit two-step invocation pattern (call without payment_signature for a free quote, then retry with the wallet-signed base64 PAYMENT-SIGNATURE) and routes price questions to list_services. It does not state explicit when-not-to-use conditions or contrast with alternatives beyond list_services.

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?

Discloses critical behavioral traits: no charge without payment_signature, requires a signed authorization from an operator, and advises retrying with the same URL and signature. Also warns about uncertain responses and avoiding duplicate payments. These go beyond annotations, which only state non-readOnly and non-destructive.

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 but packs a lot of essential info into a few sentences. Front-loads the purpose and payment method. Slightly dense with multiple warnings, but 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?

For a paid service with potential payment complexities, the description covers prerequisites (payer wallet, operator authorization), protocol (x402), error handling (uncertain response), and pricing (list_services). No output schema exists, but the tool's primary output (llms.txt draft or payment requirements) is implied. Complete for correct invocation.

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 covers both parameters fully (URL is required, payment_signature is optional). Description adds meaning: clarifies payment_signature is a base64 x402 v2 PAYMENT-SIGNATURE from a payer wallet, and that omitting it yields a quote. This enhances the schema's brief descriptions.

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 drafts an llms.txt file, uses a paid x402 service, and requires a URL. It distinguishes itself from siblings by mentioning the payment flow and the need to call list_services for pricing, though it doesn't explicitly differentiate from other run_* 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?

Provides detailed when-to-use instructions: omit payment_signature for a quote, include it after wallet signing, read list_services for current price. It also gives a critical when-not-to: never send a private key, and warns against creating another payment on uncertain responses.

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 only carry readOnlyHint=false, idempotentHint=false, and openWorldHint=true. The description adds the essential behavior: this is a paid service, the unsigned call is free and returns payment requirements, a valid x402 signature is required, private keys must never be sent, and retries should reuse the same URL and signed authorization. This is exactly the kind of non-obvious behavioral context annotations cannot express.

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 information-dense, covering purpose, payment flow, security, retry semantics, and pricing in about sixty words. The opening fragment 'Structured data pack.' is redundant with the title, so it does not fully earn a 5.

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 paid two-phase tool, the description covers the full invocation sequence, quote behavior, retry safety, and security constraints. No output schema exists, so a brief description of the returned pack's shape would have been useful, but the operational protocol is complete enough for an agent to call both phases 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%, so the baseline is 3. The description adds operational meaning beyond the schema: payment_signature should be omitted for a quote, the URL and signed authorization must remain stable on retry, and the signature value is a base64 x402 authorization rather than a private key. That is meaningful added context.

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 title and description clearly point to producing a 'structured data pack', and the schema shows the URL input, but the description starts with a noun phrase rather than an explicit verb like 'generates' or 'extracts' the pack from the URL. It does not contrast this tool with related siblings such as read_page or run_llms_txt_draft, so it stops short of a 5.

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 concrete two-phase workflow: call without payment_signature to receive requirements, have a wallet sign them, then retry with the signature. It also directs the agent to list_services for the current price and warns not to create a second payment after an uncertain response. It lacks a broader when-not-to-use statement versus the read/generation siblings, so not a 5.

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 provide readOnly, openWorld, idempotent, and non-destructive hints. The description adds context beyond that by explaining the sitemap-based search scope and that it returns URLs with a match score, which aids behavioral understanding without contradicting 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?

Two sentences deliver the core purpose, search scope, and return type with no filler. The most important constraints are front-loaded, making the description easy to scan.

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 low-complexity tool with rich annotations, the description is nearly complete: it states the target domain, search mechanism, and return format. Minor gaps remain, such as the meaning of 'match score' and the effect of 'limit', but nothing blocks a correct invocation.

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?

With 0% schema description coverage, the description must compensate for the schema's bare parameter definitions. It does so for the key 'query' parameter by clarifying that it matches words in the URL path. The 'limit' parameter is not discussed, but its meaning is self-evident from 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 uses a specific verb ('Find') with a clear resource ('pages on blacklabelbots.com') and a precise search mechanism ('words in their URL path (sitemap search)'). It also specifies the return value ('URLs with a match score'), making it easy to distinguish from siblings like read_page or site_info.

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 establishes when to use the tool: when you need to find pages by words in their URL path. However, it does not explicitly name alternatives or state when not to use this tool, so it falls short of the top score.

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 this as read-only, open-world, idempotent, and non-destructive, so the description does not need to repeat safety behavior. The description adds that the result includes links to various site documents, which is useful context. It does not describe the exact response format, but annotations cover the main behavioral risk.

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 immediately states the tool's subject and lists the types of links included. It is front-loaded with the core purpose and contains no filler or redundant phrasing.

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 zero-parameter, read-only tool with rich annotations, the description provides enough context for an agent to select and invoke it. It names the site and the types of links returned, though the exact output structure is not specified. Given the absence of an output schema)SkipThisline, the definition is nearly complete.

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 tool has zero parameters accruing to a baseline of 4. The schema confirms no inputs, and the description does not need to explain parameter behavior. No semantic gap exists because there is nothing to configure.

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 that the tool returns information about Black Label Bots (blacklabelbots.com) including links to sitemap, docs, contact, and discovery documents. It is distinct from sibling tools like list_products or read_page because it targets the overall site rather than a specific resource or action. It lacks a strong action verb but is still 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?

Usage is implied by the description: an agent would use this when the user asks about Black Label Bots or wants site-wide links. There is no explicit statement about when not to use it or which sibling tool to prefer instead. The guidance is adequate for a simple informational endpoint but not explicit.

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