NodeProxy Web Surface Markdown Parser

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

With no annotations, the description must disclose behavioral traits. It reveals the use of a headless browser, realistic browser profile, full rendering, and return of Markdown. It also mentions pricing and limitations. However, it omits specifics like error handling, timeout behavior, or rate limits, which would make it more 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, well-structured sentence that fronts the core action and purpose. It efficiently includes target use cases, limitations, and pricing without 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?

Given the tool's simplicity (one parameter, no output schema, no annotations), the description provides all necessary context: what it does, when to use it, its limitations, and cost. It adequately answers the key questions an agent would have.

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 single parameter 'url' with 100% description coverage, providing a clear definition ('Protected http(s) URL to fetch via stealth pipeline'). Baseline is 3; the tool description does not add additional parameter 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 clearly states the tool performs a hardened headless-browser fetch with JS/SPA rendering and returns Markdown. The title 'Stealth Anti-Bot' and the mention of 'light bot checks' distinguish it from the sibling surface_markdown_parser, which likely handles simpler pages.

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 the tool is best for JavaScript-heavy/SPA pages and light bot checks, and explicitly warns it is not guaranteed against advanced anti-bot walls like Cloudflare/Akamai. This provides clear 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?

With no annotations, the description bears the full burden. It transparently describes the fetch, noise removal, compression, and LLM optimization, and includes pricing. However, it does not mention error handling, side effects, or rate limits, which would improve transparency.

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 with two meaningful sentences. The first sentence explains the core action and output, and the second provides pricing. No superfluous information is included.

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 the main functionality. However, it lacks differentiation from the sibling and does not describe error behavior or output format details, making it adequate but not comprehensive.

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 'url' parameter described as 'Public http(s) URL to fetch and convert'. The tool description adds no further detail about the parameter beyond what the schema provides, so it meets the baseline of 3.

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 fetches any public URL and returns cleaned Markdown, with specific verbs and resource. However, it does not explicitly distinguish from the sibling 'stealth_markdown_parser', leaving some ambiguity about when to use each.

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 provided on when to use this tool versus the sibling 'stealth_markdown_parser' or any alternative. The description only states what the tool does without usage context.

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