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Glama

Browser Extract

browser_extract

Pull structured data from web pages as tables with headers, links, or text. Specify kind and selector to target specific elements.

Instructions

Pull structured data: kind = table (headers + row dicts) | links | text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNotable
limitNo
deviceNo
sessionNodefault
selectorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals the return shape for the table kind, but does not state whether the operation is read-only, whether it requires an active page, whether it scrolls or navigates, or what happens on failure. This is a notable gap for a tool with zero annotation coverage.

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?

A single dense sentence with no filler. The pipe-separated list is efficient and front-loads the core decision (which kind to extract). Every word adds signal.

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

Completeness2/5

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

With 5 parameters, no schema descriptions, and no annotations, a one-line description is not complete. It omits how to target an element (selector), how to bound results (limit), and how to specify device/session. The output schema may cover return values, but the tool's overall behavior and parameter roles are underdocumented.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the schema's silence. It explains the 'kind' parameter with its three values and the table row/header structure, but says nothing about 'limit', 'device', 'session', or 'selector'. The majority of the five parameters remain undocumented.

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

Purpose4/5

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

The description states a specific verb ('Pull') and resource ('structured data'), and enumerates the exact output kinds: table with headers and row dicts, links, and text. This makes the primary intent clear, though it does not explicitly differentiate from sibling tools like browser_read or browser_find.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives. The description implies it is for extracting structured content from the current page, but it does not state selection criteria, prerequisites, or when to prefer browser_read, browser_find, or other sibling tools.

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