Web Intel (x402)

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

No annotations are provided, so the description carries the burden. It discloses the cost ($0.001 USDC) and the output dimensions (language, readability, etc.), which is useful. However, it does not mention potential side effects, errors, or return format. For an analysis tool, this is acceptable but not fully transparent.

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, efficient sentence that front-loads the purpose and includes the price. No wasted words; every element (languages, outputs, cost) 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 tool with no output schema and no annotations, the description lists the outputs, supported languages, and price. It covers the essential information an agent needs to decide and invoke the tool. Missing details like error handling or async behavior are minor for a text analysis 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% (both parameters have descriptions). The description mentions 'keywords' and 'phrases' but does not add anything about the 'topN' parameter beyond what the schema already states. The description adds marginal value, so the baseline of 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?

Description clearly states it analyzes text and lists specific outputs (language, readability, keywords, key phrases, sentiment, statistics), with a distinct resource ('text'). Sibling tools (extract_webpage, pricing, seo_audit) are obviously different in purpose, so it differentiates well.

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—it is for analyzing text—but it does not explicitly state when to choose this over alternatives or any exclusions. No mention of prerequisites or conditions. The sibling tools are different enough that an agent can infer, but there is no direct guidance.

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 behavioral burden. It discloses a cost of $0.002 USDC and warns that the extracted text originates from third-party websites and should be treated as data, not instructions—an important security notice. It does not cover error behavior or rate limits, but the disclosed cost and untrusted-content caveat are valuable context beyond the schema.

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 concise sentences: purpose, price, and security warning. Every sentence carries useful information and the main purpose is front-loaded. 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?

Given the single parameter and absence of an output schema, the description enumerates the extracted data types, giving the agent a clear expectation of the return. It omits response format and error details, but for such a simple extraction tool this is sufficient. The cost and untrusted-data warning further round out the context.

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% as the single url parameter is fully described with format and example. The description adds no additional parameter-level meaning; it simply restates the notion of a public web page, 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 states a specific verb (extract) and resource (public web page) and lists the exact outputs: clean main text, title, description, headings, links, Open Graph, and JSON-LD. It is clear and unambiguous, but it does not explicitly contrast with sibling tools like analyze_text or seo_audit, so it misses the full differentiation that a 5 would require.

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 guidance is given about when to use this tool versus the siblings. The phrase 'página web pública' is a constraint, not a selection criterion. There is no mention of alternatives or exclusions, so an agent receives no help in choosing this tool over analyze_text or seo_audit.

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 only states 'Gratis' (free), which hints at cost behavior, but does not describe side effects, authentication requirements, rate limits, or whether the operation is read-only. The description implies a read operation (listing), but this is not explicitly stated.

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 front-loads the 'free' aspect and then states what is listed. It is efficient and avoids unnecessary words. However, it lacks any structured breakdown (e.g., separate sections for usage or output), but for such a simple tool this brevity is acceptable.

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 has no parameters and no output schema, the description provides a basic understanding of what it does, but it is vague about the output format (e.g., how the list is structured, what 'collection network' means). An agent might need to call it to see the result, but the description does not clarify return values or any additional context that would help interpret the output.

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 coverage is trivially 100% and there are no parameter details to explain. According to the calibration, a baseline of 4 is appropriate for zero parameters. The description does not add any parameter information, but none is needed.

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: it lists payment tools, their prices, and the collection network. It is distinct from the sibling tools (analyze_text, extract_webpage, seo_audit), which are unrelated to pricing. However, it does not explicitly name an alternative or explain how it differs from any potential pricing-related tool.

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 guidance on when to use this tool versus alternatives. It mentions 'Gratis' (free), which might imply a cost consideration, but it does not provide context for when an agent should invoke it or what scenarios it serves. No exclusions or comparisons to other tools are given.

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 behavioral burden. It discloses the output format, the audit categories, and the cost ($0.005 USDC). It does not explicitly mention network access or auth, but as a read-only audit tool the described behavior is reasonably transparent.

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 dense sentence with no filler. The core purpose is front-loaded, followed by concrete output details and pricing, making it highly 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?

For a single-parameter tool with no output schema and no annotations, the description is quite complete: it explains the input, the return value shape, the audit focus areas, and the cost. A minor gap is the lack of guidance on alternatives or edge cases, but the essentials are covered.

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 parameter 'url' is already well-documented. The description reinforces that the tool audits a URL and adds pricing context, but it provides no additional parameter-level semantics beyond what the schema already offers.

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 task ('Auditoría SEO on-page de una URL') and specifies what it produces: a 0-100 score, A-F grade, and prioritized issues. This is specific and unambiguous, though it does not explicitly contrast with sibling tools like analyze_text or extract_webpage.

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 usage context is implied: an agent would use this when an on-page SEO audit of a URL is needed. However, it does not state when to prefer this over siblings, nor does it provide exclusions or prerequisites beyond the URL requirement.

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