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Llamatron2112

mcp-dom-extract

inspect_page_structure

Fetch a web page and get a condensed DOM outline with tags, ids, classes, and text samples to identify relevant CSS selectors without loading the full page.

Instructions

Fetches a web page and returns a condensed structural outline of its DOM (tags, ids, classes, short text samples, repeated siblings aggregated). Lets the model pick relevant CSS selectors without loading the full page into context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
max_nodesNoMaximum number of outline entries
max_text_lengthNoMaximum length of each text sample
Install Server

TDQS

A4/5.0
Behavior3/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It explains the main behavior (fetching and condensing the DOM), including notable aggregation of repeated siblings. However, it does not disclose possible failure modes, network effects, rendering behavior, or limits on page size/complexity, leaving some gaps for an online operation.

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

Conciseness5/5

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

The description is a single, front-loaded sentence that wastes no words. It states the action, the output, key structural features, and the practical purpose, making every phrase informative.

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

Completeness4/5

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

Given there is no output schema, the description reasonably explains what the tool returns and why it is useful. It would be stronger with a note about failure/error behavior or relationship to discover_selectors, but it otherwise gives an agent enough context to invoke the tool appropriately.

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

Parameters3/5

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

Schema description coverage is 67%: max_nodes and max_text_length have descriptions, while url relies on its format type. The tool description does not explicitly clarify parameter usage, but it implies 'url' via 'Fetches a web page' and gives context for size limits through 'condensed' and 'short text samples'. This is adequate but not especially enriching beyond the 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?

The description states a specific verb ('Fetches'), resource ('web page'), and output ('condensed structural outline of its DOM'), and connects it to the distinct goal of picking CSS selectors. This clearly separates it from siblings like extract_page_text, which would focus on textual content rather than structure.

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?

'Lets the model pick relevant CSS selectors' gives a clear use context, and 'without loading the full page into context' provides a motivation for choosing it. It does not explicitly mention alternatives or when not to use it, but the context is sufficiently clear for an agent to make a reasonable choice among siblings.

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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