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Fetch and render any URL with JavaScript execution, auto-extract JSON-LD data from HTML, and return compact blockmaps for LLM agents.

Instructions

Fetch a URL with Chrome-fingerprinted HTTP using the active profile. Parses HTML, seeds the JS DOM, returns BlockMap inline. With exec_scripts: true, extracts inline AND external tags from the parsed HTML, fetches externals in parallel (8s per-fetch timeout), eval's them in document order in QuickJS (with shims for setTimeout/fetch/etc.), then settles the event loop and fires DOMContentLoaded + load. <script async> is honored: async scripts execute after the sync queue. When --policy=blocklist is set, tracker URLs are blocked at script-fetch time (see scripts.policy_blocked in the result). Returns a scripts summary with inline_count, external_count, async_count, policy_blocked, executed, errors.

Auto-extract: when the page embeds JSON-bearing tags (density.json_scripts > 0 — covers application/json, application/ld+json, text/x-magento-init, text/x-shopify-app, etc.), navigate auto-runs extract() and returns the result as the extract field. Saves a round trip on the common case where the data the JS would have rendered is already sitting in the HTML — JSON-LD article schemas on news sites, NEXT_DATA page state on Next.js apps, json_in_script product blobs on Magento/Shopify, GitHub RSC payloads, etc. Capped at 256 KB inline; over that limit extract returns a stub with strategy/confidence/size_bytes/hint and the agent should call extract() explicitly to retrieve the full payload. Pages with no embedded JSON get extract:null and pay zero extra cost.

Tool advice: navigate also returns tool_likelihoods plus tool_recommendations, derived from concrete page signals (structure/headings, selector hints, density, embedded data, network captures, challenge state, and script pathology) so agents can pick the next tool without guessing.

Auto-solve: Reddit's JS proof-of-work challenge (provider: reddit_js_challenge) is transparently solved — the challenge is detected, the GET solution URL is computed (solution = hex_value + hex_value), and the real page is returned in one navigate call. challenge:null on the result means the real page was served. Subsequent navigations in the same session carry the clearance cookie and skip the challenge entirely.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
exec_scriptsNoRun page <script> tags (inline + external src) after parse, settle the event loop, and fire DOMContentLoaded + load. Default false.
urlYesAbsolute URL to fetch
Behavior5/5

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

No annotations provided, so description fully discloses behavior: script execution details, auto-extract logic with size cap, auto-solve for Reddit challenges, and clearance cookie persistence. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear sections (Auto-extract, Tool advice, Auto-solve), but lengthy. Every sentence adds value; no fluff. Appropriate length for complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers return values (BlockMap, scripts summary, extract field, tool_likelihoods) and special cases (size cap, challenge handling). No output schema provided, but description compensates fully.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Input schema has 100% coverage, baseline 3. Description adds significant detail for exec_scripts (how scripts are fetched and evaluated) and explains auto-extract behavior that depends on URL content, enhancing schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it fetches a URL with Chrome-fingerprinted HTTP using the active profile, and details script execution and auto-extraction. Differentiates from siblings like extract, click, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides guidance on when to use auto-extract vs explicit extract, and mentions tool_recommendations for next steps. Lacks explicit when-not-to-use or direct sibling comparisons.

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

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