CleanPage

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

With no annotations provided, the description fully carries the behavioral disclosure burden. It reveals that the tool is paid ($0.02 USDC via x402), explains the two-step payment flow, promises typed errors for common failure modes instead of 'silently returning junk', and states that failed extractions are not charged. This is far beyond the minimum.

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 relatively long but well-structured: core function and outputs first, then failure-mode handling, then payment details. Every sentence carries useful information. A bit dense, but the payment flow and output enumeration justify the length.

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?

Without an output schema, the description compensates by enumerating all return components (markdown, plain text, metadata, links, images, facts, quality score). It also covers payment behavior, error policy, and charging rules, so an agent has enough context to correctly invoke the tool and interpret results. 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 schema already provides descriptions for the required url and every nested option property (language, max_length, timeout_ms, extract_facts, include_images). The description adds only implicit hints, such as matching 'optional structured facts array' to extract_facts. Since schema covers most parameters, the description does not need to compensate much but also does not add significant parameter-level meaning.

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 verb and resource: 'Fetches a URL and returns clean, structured, agent-optimized content' with a detailed breakdown of outputs (markdown, metadata, links, images, facts, quality score). Clearly distinguishes itself from sibling tools health, list_capabilities, and pricing, which serve entirely 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?

Provides clear context for when to use the tool (when you need to extract clean content from a URL) and includes important usage flow guidance (drop a no-payment call first to get 402 requirements, then retry with X-PAYMENT header). Does not explicitly state when not to use it or compare to alternatives, but siblings are unrelated, so the context is sufficient.

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 full burden. It discloses the tool is 'Free' and returns status, version, and uptime, which is meaningful behavioral context. It doesn't describe response format or error behavior, but for a zero-parameter health check this is reasonably sufficient.

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, no waste, and the key behavioral attributes ('Free', returns status/version/uptime) are front-loaded. 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 zero-parameter health check, the description covers the essentials: what it returns and when to use it. It could mention error handling or exact output schema, but the simplicity of the tool makes it complete enough. Siblings are clearly distinct.

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?

There are zero parameters, so the baseline is 4. The description adds no parameter-level detail, but none is needed. Schema coverage is 100% trivially since there are no properties.

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 returns service status, version, and uptime signal, using a specific verb ('returns') and resource. This distinguishes it from siblings like pricing or clean_page, which clearly serve different purposes. An agent can immediately identify this as a health check.

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 explicit when-to-use guidance: 'Use to check the service is reachable before paying for anything.' This gives a clear context and an exclusion (before paying), making usage intent unambiguous.

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 explicitly discloses that the call is 'Free,' a key behavioral and cost trait, and states exactly what will be returned. It does not mention rate limits or auth, but for a zero-parameter read-only listing tool the disclosed traits are sufficient and non-contradictory.

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 sentence front-loads the most important fact ('Free'), then states the action, the response contents, and the agent-facing value. There is no filler, repetition, or 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 simple, parameterless tool with no output schema, the description covers the return content (tool list, prices, schemas) and when to use it. It could more explicitly differentiate from the sibling 'pricing' tool, but an agent has enough context to call this correctly before spending anything.

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 input schema has zero parameters, so there are no parameter meanings to clarify. The 100% schema coverage means the schema is complete, and the description appropriately adds no parameter noise. Baseline 4 applies because no parameters exist to document.

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 states a specific verb and resource: 'Returns the full list of tools this server offers.' It enumerates what the response includes (paid status, prices, input schemas) and assigns a purpose ('so an agent can decide what to call'). This clearly distinguishes it from the sibling 'pricing' tool, which would only provide pricing details without the full capability catalog.

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 'before spending anything' gives a clear usage context: invoke this tool when deciding which paid tools to call. However, it does not explicitly name alternatives such as 'pricing' or state when not to use this tool, so it stops short of full exclusions and alternative routing.

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 burden. It discloses that the tool is 'Free' and that it returns specific pricing/payment data, which implies a read-only operation. However, it does not mention authentication, rate limits, or whether the data may be cached or delayed.

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, compact sentence with no filler. The 'Free' qualifier is front-loaded and the return content is listed in a logical order, 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 simple, parameterless tool without an output schema, the description covers enough: it states cost, return categories, and the tool's scope ('for paid tools'). The only minor gap is that 'x402 payment flow details' is left slightly undefined, though it is likely domain-specific terminology.

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 requires no documentation. The description appropriately focuses on return content rather than input semantics, matching the baseline for parameterless tools.

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 a specific verb ('Returns') and a precise resource: current pricing, accepted payment network/asset, and x402 payment flow details for paid tools. This clearly differentiates it from sibling tools like clean_page, health, and list_capabilities.

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 purpose strongly implies when the tool should be used, but the description does not explicitly state conditions or name alternatives. An agent can infer the use case from the content, but no explicit guidance is provided.

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