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KitchenSink4AI

KitchenSink4Web

Official

get_page_view

Read-only

Reads a webpage to provide a concise orientation summary, listing key regions, interactive elements, and missing content, while respecting a token budget.

Instructions

Read a page as an ORIENTATION, not a transcript, under a token budget it never exceeds whatever the page size. Returns identity, landmark regions each priced with the cost to expand it, the interactive surface with refs you can act on, a digest or app skeleton, form and table inventories, an account of what was NOT read and why, and the next call for anything unexpanded. location scopes to one region ref, budget_tokens=2500 suits a subagent, mode='links' includes in-prose links at their real cost. since=<read_token> is the cheap repeat read: only what changed, refs kept, a few hundred tokens instead of a fresh read, and it falls back to a full read when the page navigated in between and nothing survives to diff. Open shadow roots are read and their contents get refs you can act on; closed roots cannot be reached by any tool and are counted at creation, so the completeness block reports both numbers rather than one confident zero. Same-origin iframes are entered and read, and their contents get refs naming the frame they came from; a cross-origin frame is never entered, because its document belongs to an origin the page itself cannot read either, and the completeness block counts every frame it did not open.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoauto
pageYes
viewNoauto
sinceNo
detailNostandard
locationNo
budget_tokensNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.6/5.0
Behavior5/5

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

Even though annotations already declare readOnlyHint=true, the description goes far beyond that: it details token-budget guarantees, fallback behavior for since tokens, handling of shadow DOM (open vs closed), same-origin vs cross-origin iframes, and the completeness block counting unread content. This is rich, candid behavioral disclosure that helps an agent predict side effects and limitations.

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?

The description is long but structured as a dense, information-rich paragraph with logical flow from output composition to specific parameter modes to edge-case behaviors. Every clause adds substantive detail about capabilities or limitations; it is not padded, though it could arguably be tightened without losing meaning.

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?

Given the tool's complexity, the absence of an output schema, and 0% schema parameter descriptions, the description is exceptionally complete. It covers what is returned, how tokens are managed, what happens with shadow DOM and iframes, how to perform cheap repeat reads, and what the completeness block reports. An agent has enough information to call this tool correctly in most scenarios.

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?

With 0% schema description coverage, the description is the only source for parameter meaning. It explicitly explains 'location', 'budget_tokens', 'mode', and 'since' with usage context, and 'page' is self-evident. However, it leaves 'view' and 'detail' completely unexplained, which is a gap for a tool with 7 parameters, though the core behavioral parameters are well covered.

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?

The description opens with a clear, specific verb ('Read') and resource ('a page') and immediately distinguishes it from a transcript by calling it an 'ORIENTATION'. It also enumerates the specific output components (identity, landmark regions, interactive surface, etc.), making the tool's function unambiguous and distinct from siblings like get_text.

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?

The description provides strong context for when to use the tool: it positions it as an orientation with a token budget, and gives concrete parameter guidance (e.g., 'budget_tokens=2500 suits a subagent', 'mode='links' includes in-prose links', 'since=<read_token> is the cheap repeat read'). However, it does not explicitly name alternative sibling tools or state when not to use it, leaving the comparative routing implicit.

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