x402-vend — WebIntel

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

No annotations are provided, so the description fully carries the burden. It discloses that the call costs $0.10 via x402 on Base, describes the output as 'synthesised judgment, not raw data', and lists all output components with confidence and evidence quotes. This is comprehensive behavioral disclosure.

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 paragraph of about four sentences, front-loaded with the name and pricing. Every sentence provides value without fluff, efficiently conveying purpose, output, pricing, and differentiation.

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 no output schema, the description thoroughly explains the return fields (what company does, category, audience, business model, market, language, analyst take, sales hook, confidence, evidence quotes). It also covers pricing and access, making the tool's behavior fully understandable for an AI agent.

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 schema has 100% description coverage for the only parameter 'domain' (described as 'Domain name, e.g. example.nl'). The tool description adds little beyond 'Give it a domain', 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 'Get an AI analyst's read on a company from its homepage' and lists specific outputs (e.g., category, audience, business model, etc.). It distinguishes itself as the 'qualitative complement to /enrich and /report', ensuring no confusion with 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?

The description explains when to use (for a qualitative company assessment from a domain) and references sibling tools as complements. It does not explicitly state when not to use, but the context is clear. Pricing and no account requirement are also noted.

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 provided, so the description carries full burden. It discloses the cost ($0.02 per call via x402) and that no account is needed. However, it does not explicitly state that the operation is read-only, nor mention throttling, error responses, or behavior for invalid domains. The behavioral context is moderately informative but incomplete.

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 few sentences long, front-loading the cost and purpose. It is structured with a clear flow: cost, functionality, use case, account requirement. Every sentence adds value, though the cost detail could be more concise.

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 the tool's simplicity (one parameter, no output schema), the description explains the return value types (records, SPF, DMARC, host) and even highlights EU/NL host recognition. However, it lacks details on response format and error handling, which would make it more 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?

Schema coverage is 100% with a single parameter 'domain' that already includes a description and example ('e.g. example.nl'). The tool description adds no extra meaning beyond the schema, 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 clearly states the tool provides DNS and email intelligence for any domain, listing specific record types (A/AAAA/MX/NS/TXT) and detected email provider. The verb 'intelligence' and resource 'domain' make the purpose specific and well-defined, and it stands out from sibling tools like whois or sitemap.

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 use cases: deliverability checks and qualifying leads, and mentions recognition for many EU/NL hosts. It implies when to use the tool but does not state when not to use it or provide alternatives, though the sibling tools list is diverse so confusion is unlikely.

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 cost ($0.10 per call), payment method (x402 USDC), no account/API key needed, and what data is returned (company name, VAT, KvK, etc.). Missing details on rate limits or error handling.

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 paragraph that front-loads key information (purpose, cost, region). It is not overly verbose, though it could be more structured with bullet points. It earns its length by providing necessary details.

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 tool with one parameter and no output schema, the description covers purpose, input, output, cost, and use case. It misses potential failure scenarios (e.g., invalid domain) but is otherwise complete for its complexity.

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% with a single parameter 'domain'. The description adds the example 'example.nl' and explains its use, but does not significantly extend the schema's description. 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 enriches companies from domain, specifically for EU/NL. It uses a specific verb 'enrich' and resource 'company', and distinguishes from siblings by focusing on EU data like VIES, KvK, and BTW.

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 says 'Ideal for qualifying EU/NL leads', implying when to use. It contrasts with 'generic US enrichers' but does not explicitly state when not to use or mention alternatives among siblings like 'assess' or 'lead_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?

With no annotations, the description fully discloses pricing ($0.15 per call via x402), that no account/API key is needed, and it fuses EU company enrichment with domain age. It also describes the output format clearly.

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 somewhat lengthy but front-loads key info (pricing, purpose). Each sentence adds value, though slight trimming could improve conciseness without losing substance.

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 the tool's complexity (scoring, enrichment, pricing, no account), the description covers all essential aspects. Without an output schema, it still details the return value (score, band, reasons), making it 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?

Schema coverage is 100% for the single 'domain' parameter, and the description adds context that it is for B2B lead scoring from a domain, with EU/NL focus. This provides meaningful extra meaning beyond the schema's bare 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 clearly states the tool scores and qualifies a B2B lead from a domain, returning a 0-100 score with hot/warm/cold band and reasons. It distinguishes itself from siblings (e.g., enrich, dns) by focusing on lead scoring specifically for EU/NL companies.

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 notes it is 'built for sales and lead-gen agents prioritising EU/NL companies' and explains the pay-per-call model. However, it does not explicitly mention when not to use this tool or suggest alternatives among siblings.

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 provided, so the description carries full burden. It discloses cost and authentication requirements but does not mention error handling, rate limits, or what happens with invalid URLs.

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?

Three sentences, front-loaded with purpose and pricing. Every sentence adds value 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?

Given the simple tool (one parameter, no output schema), the description provides sufficient context including the types of metadata extracted. It could mention output format, but the lack is not critical.

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 the single 'url' parameter (100%). The description repeats 'Give it a URL' but adds no additional meaning beyond the schema's 'Full http(s) URL'.

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 it extracts structured metadata from a URL, listing specific types (title, meta description, OG tags, etc.). The verb 'extract' is precise. It distinguishes from siblings like 'read' or 'assess' by focusing on metadata extraction.

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 explains when to use (give a URL for metadata) and mentions pricing and no account needed. However, it does not explicitly contrast with sibling tools or state when not to use it.

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 exist, so the description carries the full burden. It discloses pricing ($0.01 per call, x402 payment), authentication requirements (none), and output format (markdown). It does not mention rate limits or error handling, but the disclosed behavioral traits are valuable.

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 highly concise: four sentences front-loaded with purpose, then cost, output details, and use case. Every sentence adds value 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?

Given the simple tool with one parameter and no output schema, the description covers input (URL), output (markdown), behavior (preservation/stripping), cost, and authentication. It is complete for the tool's complexity.

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 baseline is 3. The description reinforces the URL parameter and adds context about using it for web pages, but does not add significant new meaning beyond the schema's 'Full http(s) URL'.

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 turns any web page into clean markdown, preserving specific elements and stripping clutter. It distinguishes itself from sibling tools like 'dns' or 'whois' by focusing on page content reading.

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?

It explicitly states 'Ideal for feeding page content to an LLM,' providing a clear use case. However, it lacks explicit when-not-to-use guidance or direct comparisons with sibling tools, but the use case is sufficient 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?

With no annotations, the description carries full burden. It discloses pricing ($0.25 per call, x402 USDC on Base), live computation, and no account/API key needed. It does not mention rate limits, data freshness, or potential size of response, but the cost and authentication model are well-covered.

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 four sentences long, front-loading purpose and pricing, then listing contents. Every sentence adds value, no redundancy, and the structure is 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?

Given the tool's complexity (domain dossier with multiple data types) and absence of an output schema, the description explains the output contents explicitly (tech stack, DNS, email-provider intel, etc.). It could be more complete by mentioning response format or pagination, but it is sufficient for a general understanding.

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% for the single 'domain' parameter, with a basic example provided in the schema. The description adds no additional constraints or semantics for the parameter beyond what the schema states, but it does contextualize how the parameter is used in the broader tool purpose. 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's purpose: 'Get a complete intelligence dossier on a domain in one call.' It lists specific data types (tech stack, DNS, email-provider intel, etc.) and distinguishes from sibling tools by positioning it as an all-in-one alternative to chaining several calls.

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 provides clear usage context: 'when you'd otherwise chain several calls.' It implies this tool consolidates functionality of siblings like dns, whois, sitemap, etc. However, it doesn't explicitly state when to use individual tools instead, but the guidance is sufficient for decision-making.

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. It discloses cost ($0.01 per call, x402 USDC), no account needed, limit of 500 pages, and source (robots.txt, sitemap.xml). This covers key behavioral aspects, though it omits details like rate limits or error handling.

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, front-loading purpose and cost, then providing usage context. Every sentence adds value, with no extraneous text. Perfectly structured for quick understanding.

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 the tool's simplicity (one parameter, no output schema), the description is complete. It explains what the tool returns (list of URLs up to 500 pages), how it works (via robots.txt and sitemap.xml), and important context (cost, no account needed). No gaps remain.

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% with a clear description for the single parameter 'domain' (e.g., example.nl). The description adds 'Give it a domain' but does not provide additional semantic value beyond the schema. 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 discovers all pages on a website by providing a domain and returns its list of URLs, specifying the method (robots.txt, sitemap.xml) and limit (500 pages). This differentiates it from sibling tools like assess or dns which serve different purposes.

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 usage guidance: 'Use it to map a site's structure before crawling or to find which pages are worth reading.' It implies when to use (site mapping) but does not explicitly state when not to or compare alternatives, making it slightly less than 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?

Discloses cost ($0.05 per call, x402 USDC on Base) and states 'no account, no API key'. No annotations provided, so description bears full burden. Does not mention rate limits or response format, but adds useful financial/friction info.

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?

Description is well-structured but slightly verbose (multiple lists). Front-loaded with purpose and cost. Could trim some repetitive categories, but remains clear and scannable.

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?

Covers tool purpose, usage, cost, and expected input. Lacks explicit output format (no output schema), but lists detected categories sufficiently for an agent. Minor gap in return value description.

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?

Single 'domain' parameter with schema coverage 100%. Description reinforces parameter meaning with example and context. Adds no additional syntax but is sufficient.

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?

Description clearly states the tool detects technology stack behind websites, listing specific categories (CMS, e-commerce, etc.). Distinct from sibling tools like 'assess' or 'dns' which serve different purposes.

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 says 'Give it a domain and find out...' and provides use cases: technographics, competitor research, lead enrichment. Lacks direct contrast with sibling tools but context is 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?

Discloses cost, payment method, and source (VIES), but lacks details on failure modes, rate limits, or error responses.

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 sentences, front-loaded with purpose, cost, and usage context. No unnecessary words.

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?

Explains return values (validity, company name, address) and typical use cases, but does not specify behavior for invalid inputs or edge cases.

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 already describes parameter with example; description adds context about format and usage, but does not significantly expand beyond 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?

Clearly states the tool validates EU VAT numbers against official service, with examples. No explicit sibling differentiation, but siblings are unrelated.

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?

Implies usage for invoicing, onboarding, KYB, and compliance, but lacks explicit when-not-to-use or alternatives.

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 transparency burden. It discloses the cost model ($0.02 per call via x402), the use of RDAP and authoritative registry, and lists the return fields (registration date, age, registrar, etc.). It could mention rate limits or error handling, but the key behaviors are covered.

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 sentences plus a pricing note and usage line, efficiently front-loading the primary action. It is concise without unnecessary detail.

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 one parameter and no output schema, the description explains the return values (registration date, age, registrar, etc.), cost, and use cases. It is complete enough for an agent to understand functionality and limitations.

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% for the single parameter 'domain'. The description reinforces the parameter meaning with 'Give it a domain' and adds the x402 cost context, but does not add 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 clearly states the tool's purpose: 'Look up a domain's registration and age via RDAP.' It specifies the resource (domain registration) and action (lookup), distinguishing it from sibling tools like dns (DNS lookups) and enrich (enrichment).

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 provides context for use: 'Useful for lead qualification and trust/legitimacy scoring.' It also notes reliability for .nl/SIDN and EU ccTLDs. While it doesn't explicitly exclude other uses or compare with alternatives, the guidance is sufficient for a specialized tool.

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