x402 Web Tools

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the cost ($0.002 USDC) and the nature of the checks, which is useful. However, it does not state whether the operation is read-only, whether external data is sent, or what the response format looks like. The cost disclosure is a strong point, but the lack of side-effect or response details leaves a moderate 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?

Two sentences with zero fluff. The first sentence front-loads the action and outputs, the second gives the use case and cost. Every word earns its place, 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?

For a single-parameter tool with no output schema, the description covers the essential context: what it does, what it returns, when to use it, and what it costs. It lacks explicit error-handling or edge-case information, but the tool is simple enough that this is a minor omission rather than a critical gap.

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 already documents the single parameter 'domain' as 'Domain or full email address' with 100% coverage. The description mirrors this by saying 'email address or domain' but adds no new semantic detail about format, normalization, or edge cases. Baseline 3 is appropriate since 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 opens with a specific verb ('Check') and clearly defines the resource ('email address or domain'). It enumerates the exact outputs (MX records, mail provider, SPF, DMARC, disposable-domain flag, deliverability score), making the tool's function unambiguous and distinct from the sibling tools, which target tech stacks, webpages, and pricing.

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 phrase 'Validate leads before sending' explicitly states the primary use case. It does not mention when not to use the tool or alternative tools, but the siblings are sufficiently different that no exclusion is necessary. The guidance is clear and actionable.

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 present, so the description carries the full burden. It does disclose a significant behavioral trait: 'Costs $0.003 USDC (x402, Base),' which alerts the agent that calling this tool triggers a payment. However, it does not mention what happens on invalid URLs, whether the tool makes an outbound request to the target site, the response format, or any rate limits.

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 core action, followed by useful category examples, a use-case phrase, and the cost. Every sentence adds value: what it detects, why to use it, and what it costs. No filler 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 one-parameter tool with no output schema and no annotations, the description covers the main purpose, use cases, cost, and detection categories. However, it omits any indication of the output format or the behavior of the tool (e.g., whether it returns a report, errors on non-http(s) URLs, or how the cost is billed). This leaves the agent without a full picture of what the call returns.

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 covers the sole parameter (url) with a description 'Public http(s) URL' and 100% coverage, so the baseline is 3. The tool description adds no additional meaning beyond the schema, merely implying the URL through 'website.' There is no need to compensate for coverage 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 names the verb and resource: 'Detect the technology stack of a website' and then enumerates specific categories (frameworks, CMS, analytics, payments, CDN/hosting, server headers). This makes the tool's function specific and distinct from siblings like check_email_domain or extract_webpage in substance, though it doesn't explicitly name those alternatives.

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 explicit use contexts: 'Useful for lead qualification and competitor research.' This gives clear guidance on when to invoke the tool. It does not, however, state when not to use it or explicitly compare it to sibling tools, so it's one step short of full differentiation.

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 of behavioral disclosure. It reveals that the tool uses Readability to produce clean Markdown, lists the specific fields returned (title, description, og:image, byline, word count, outgoing links), and discloses a cost point of $0.003 USDC via x402 on Base. This goes beyond a generic 'fetch page' and informs the agent of non-obvious traits like payment and output composition. It does not cover failure modes or rate limits, but the provided information is substantial.

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 concise sentences. The first sentence front-loads the action and output, the second adds the use-case and cost. There is no redundancy or filler. Every phrase earns its place, making it easy for an agent to parse quickly.

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, no annotations), the description is quite complete. It specifies the type of URL (public), the return fields, the readability processing, and the cost. It does not address error handling, redirects, or non-HTML content, but these are minor for a fetch tool. For an LLM agent, the essential information needed to invoke and interpret the result 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?

Schema description coverage is 100%—the only parameter 'url' has a description 'Public http(s) URL'. The tool description reinforces that the page must be 'public' but does not add syntax, format details, or examples beyond the schema. Since the schema already documents the parameter adequately, the description's marginal addition is minimal. Per the baseline rule for high schema coverage, a 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 opens with a specific verb ('Fetch') and resource ('any public web page'), then enumerates the exact output (Markdown, title, description, og:image, byline, word count, outgoing links). This clearly distinguishes it from sibling tools like check_email_domain or pricing, which serve entirely different purposes. An agent knows exactly what this tool does and what it returns.

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 'Ideal for LLM agents that need page content without HTML noise', providing clear context on when this tool is appropriate. It does not explicitly name alternatives or state when not to use it, but the sibling tools are so different in scope that an agent would not confuse them. The intended use case is conveyed effectively, though explicit exclusion is 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?

No annotations are provided, so the description carries the full burden. It discloses that the tool lists prices and payment details, and states 'Free,' which may indicate cost or free access. However, it doesn't mention whether the output is a simple list, whether it requires authentication, or any rate limits. For a read-only informational tool this is adequate but not comprehensive.

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 extremely concise: two short phrases ('Free.' and 'Lists tools, prices and payment details of this server.'). It front-loads the potentially important cost hint and then specifies exactly what is listed. Every word earns its place with no 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 no parameters, no output schema, and a simple informational purpose, the description covers the essential content: what is listed and the server scope. It doesn't specify the format of prices or whether all tools are included, but these are minor for a listing tool. It is mostly complete for an agent to call it appropriately.

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, so the schema is already fully covered (100%). The description adds no parameter information because there are none, which is appropriate. Baseline for a no-parameter tool is 4, and nothing detracts from that.

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 ('Lists') and a specific resource ('tools, prices and payment details of this server'). It distinguishes this tool from its siblings (check_email_domain, detect_tech_stack, extract_webpage) by focusing on pricing/ payment info. Not a tautology and clearly informative.

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?

No explicit when-to-use or alternatives are given, but the purpose is self-evident: when an agent needs pricing or payment details of the server. The 'Free.' opener hints that cost is a relevant factor, though it doesn't clarify whether this tool itself is free or the server's tools are free. Usage is implied rather than explicitly guided.

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