Web Validator by DigestSEO

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

Annotations already mark the tool as read-only, open-world, idempotent, and non-destructive, and the description adds substantial behavioral context: robots.txt respect, page cap, same-origin boundary, no JavaScript execution, no asset fetching, no recursive link following, and deduplicated findings. This goes well beyond the structured 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?

Four short sentences carry distinct, non-redundant information: when to use, what it returns at most, what it avoids, and how to paginate. Every sentence contributes and the most important usage guidance is front-loaded.

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 output schema is present and annotations cover side effects, the description is complete for safe invocation. It covers authorization, scope, limits, exclusions, and continuation, leaving no critical operational 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?

Schema coverage is 100%, so the baseline is 3, but the description adds meaning by framing max_pages and page_offset as part of a sitemap-first bounded audit and by explaining when page_offset is needed. This gives the agent operational context beyond the individual parameter 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 states a specific verb (audit), resource (public website), and scope (bounded, sitemap-first, at most 8 same-origin HTML pages). It also explicitly lists what it does not do, distinguishing it from sibling tools like check_broken_links and audit_public_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?

It opens with an explicit 'Use this for' condition plus the authorization requirement. It clearly states what the tool will not do, signaling when a different tool is needed, and it instructs the agent to use page_offset to continue when more sitemap pages remain.

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?

Beyond the readOnly/idempotent/openWorld annotations, the description discloses the bounded single HTML fetch, the opt-in link-checking behavior, and the absence of crawling, JavaScript execution, authentication, and stylesheet fetching. These are material behavioral traits an agent needs to set expectations. 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?

Three sentences, front-loaded with the trigger condition, followed by scope, limitations, and authorization constraint. Every sentence adds value and none restate the tool name or title.

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 complete parameter schema, the presence of an output schema, and rich annotations, the description fully covers what the tool does, its safety profile, and its limitations. An agent has everything needed to select and invoke it 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?

Input schema coverage is 100%, so the parameters are already documented in the schema. The description reinforces bounded behavior and opt-in link checking, but it does not need to compensate for missing schema details. 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 opens with 'Use this when the user provides one live public webpage URL' and details the specific actions: HTML validation, SEO/accessibility-signal checks, and JSON-LD syntax checks. This makes the tool's purpose and resource unmistakable and separates it from sibling validation 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?

The description gives an explicit trigger condition ('one live public webpage URL'), explicit non-goals ('does not crawl, execute JavaScript, authenticate, or fetch linked stylesheets'), and a hard prerequisite ('only URLs the user owns or is authorized to inspect'). It also notes link checking is opt-in, preventing misuse.

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 and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond annotations by clarifying that the tool operates on raw HTML rather than fetching a live webpage, which is a key behavioral boundary.

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 filler. The primary usage instruction is front-loaded, and the exclusion/alternative is stated in the second sentence. 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?

For a single-parameter, read-only tool with an output schema and robust annotations, the description covers what the agent needs: usage intent, input type, and the key alternative route for URLs. Nothing critical is missing.

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 the parameter schema fully explains that 'html' is raw HTML markup and not a URL. The description reinforces this but does not add substantial semantic detail beyond the schema, so the baseline score 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?

The description uses a specific verb ('audit') with a clear resource ('supplied HTML') and scope ('focused SEO/accessibility-signal check'). It explicitly contrasts itself with audit_public_webpage, making sibling differentiation immediate.

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 directly states when to use this tool ('Use this for a focused SEO/accessibility-signal check of supplied HTML') and when not to use it ('It does not fetch a live webpage; use audit_public_webpage for a URL'). This is explicit, actionable 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?

Annotations already declare readOnly, idempotent, openWorld, and non-destructive hints, so the bar is lower, but the description still adds meaningful behavioral detail: it will not fetch base_url, will not follow redirects, and will not retain response bodies. These are non-obvious limits that materially shape an agent's expectations and are not captured in the annotations or 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 exactly two sentences with no filler. The primary action is front-loaded in the first sentence, and the constraints are packed into one efficient clause in the second sentence. 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 input parameters are fully documented by the schema, and the output schema covers return values, so the description only needs to carry selection-relevant behavioral context, which it does. It could define 'broken' status criteria or mention how links are extracted, but these are not required 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 description coverage is 100%, so the baseline is 3. The description's 'up to 20 public HTTP(S) links' echoes max_links and the html source, but it does not add new parameter-level meaning beyond what the schema already provides.

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 ('check'), a resource ('up to 20 public HTTP(S) links found in supplied HTML'), and a scope ('focused'), which clearly conveys what the tool does. It hints at differentiation from broader audit/validate siblings through the word 'focused' and the explicit limitation, though it never names an alternative directly.

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 opening 'Use this for' provides an explicit scenario for when to invoke the tool, and the second sentence lists exclusions (does not fetch base_url, does not follow redirects, does not retain response bodies), which implicitly tells an agent when not to use it. It does not name specific alternative tools, but the context is strong enough for 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, openWorldHint, idempotentHint, and non-destructive behavior. The description adds useful behavioral specifics: it combines Nu HTML validation with CSS, SEO, accessibility, and JSON-LD checks, and clarifies that base_url only resolves links without fetching. This adds context beyond the annotations, though it does not discuss potential rate limits or authentication, which are not covered by 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?

Three sentences with no filler. The first sentence establishes usage context, the second summarizes the tool's functionality, and the third provides a critical limitation and sibling alternative. Efficient and well-structured.

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 a rich output schema, detailed parameter descriptions, and comprehensive annotations, the description covers the primary use case, the main limitation (no fetching), and the alternative tool. Everything an agent needs to decide whether to call this tool and what it does 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%, so each parameter is well-documented in the schema. The description adds minimal param-specific meaning (e.g., 'local CSS' clarifies css scope, and the base_url limitation is also in the schema), but it does not compensate further. 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 specifies a clear verb and resource: validates supplied HTML markup with multiple checks. It explicitly distinguishes itself from audit_public_webpage by stating it does not fetch a webpage from base_url, making it easy to tell apart from 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?

States the condition for use ('when HTML markup is already supplied') and explicitly says not to use it for live URLs, pointing to audit_public_webpage as the alternative. This is explicit when-to-use and when-not-to-use 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?

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is known. The description adds that parsing happens inside the Worker (no external service) and returns syntax messages, which is useful behavioral context beyond annotations. It does not contradict any annotation.

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 with no filler. The usage trigger is front-loaded, and the behavioral detail (local parse, no external call) is succinctly stated. 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?

For a single-parameter, read-only tool with a known output schema, this description covers purpose, usage, and key behavioral traits. The output schema handles return format details, so nothing critical is missing for an agent to decide and invoke the tool 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 coverage is 100% and the parameter description in the schema already explains 'Raw CSS source supplied by the user.' The tool description adds no additional semantic detail beyond that, so the baseline 3 applies—the parameter is fully documented but the description adds little value on top.

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 action (parses CSS) and the resource (raw CSS source), clearly distinguishing it from sibling validation tools for HTML or schema markup. It also identifies the kind of input it accepts, making the tool's purpose 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?

The description explicitly states when to use the tool ('Use this when raw CSS source is supplied'), giving a clear trigger condition. It does not explicitly name alternatives or state when not to use it, but the condition is sufficient for an agent to route correctly. Missing explicit cross-references to siblings, but the 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?

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety and external dependence. The description adds the specific external service (validator.nu) and the fact that it's for raw markup, which is useful context but not a major disclosure beyond 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, front-loaded with the usage directive and purpose, with no wasted words. The alternative is mentioned concisely.

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 output schema exists, the one parameter is fully documented, and annotations cover safety, the description sufficiently explains what the tool does, when to use it, and how it differs from the closest sibling. Nothing critical is missing.

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 single 'html' parameter is fully described in the schema (100% coverage) with a clear note that it is not a URL. The description echoes this but doesn't add new semantic information, so it's at the baseline for high schema coverage.

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 (sends markup to Nu HTML Checker and returns validation messages) and the specific resource (raw HTML markup). It also distinguishes itself from audit_public_webpage, making it easy to identify.

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 states when to use the tool ('when raw HTML markup is supplied') and provides a clear alternative for live URLs ('use audit_public_webpage'). This gives the agent unambiguous routing criteria.

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 convey read-only, idempotent, non-destructive behavior. The description adds useful behavioral context beyond annotations by clarifying that only JSON is parsed and Schema.org vocabulary semantics are out of scope.

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 with no filler. It front-loads the use case and immediately states a key limitation, making it efficient and easy to parse.

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 read-only tool with a rich output schema and strong annotations, the description covers the core scope and limitations. Nothing critical needed to decide whether to invoke the tool is missing.

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%, and the parameter description already explains that html is raw markup, not a webpage URL. The tool description reinforces the input type but adds little new semantic detail 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 identifies the specific action: a focused JSON-LD syntax check of supplied HTML. It also distinguishes itself from semantic Schema.org validation, which helps an agent differentiate it from siblings like validate_html and validate_css.

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 when to use the tool: for a focused JSON-LD syntax check. It also provides an explicit exclusion by noting it does not validate Schema.org vocabulary semantics, though it does not directly name alternative tools or conditions for them.

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