extract_metadata
Extract page metadata: title, description, Open Graph, Twitter cards, JSON-LD, canonical URL, and all meta tags.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
AgentScrape
TDQS
A3.7/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations beyond a title, the description carries full burden but only lists extracted fields, not behavioral traits like HTTP requests, destructiveness, or rate limits. It is adequate for a simple tool but lacks depth.
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 sentence with no wasted words, front-loading the purpose and enumerating details efficiently.
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 the tool's simplicity (one parameter, no output schema), the description adequately covers what metadata is extracted, though it lacks details on return format or edge cases.
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?
The input schema has one parameter 'url' with 0% description coverage, and the description does not mention the parameter, leaving the agent to infer its meaning solely from 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 clearly states the verb 'Extract' and the resource 'page metadata', enumerating specific types (title, description, Open Graph, etc.), making it distinct from sibling tools like scrape_webpage or screenshot_webpage.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for metadata extraction but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or when-not-to-use scenarios.
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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Glama MCP Gateway
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TDQS
A3.7/5.0
Disambiguation5/5
Each tool serves a distinct purpose: session management, metadata extraction, AI-powered data extraction, multi-step workflows, content scraping, and screenshot capture. There is no overlap or ambiguity.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern with underscores (e.g., create_browser_session, extract_metadata, run_workflow), making it predictable and easy to understand.
Tool Count5/5
With 6 tools, the server covers the essential operations for web scraping and automation: session management, content retrieval, metadata extraction, structured data extraction, screenshots, and complex workflows. The count is well-scoped and not excessive.
Completeness4/5
The tool set covers core scraping tasks comprehensively, including advanced workflow automation. Minor gaps exist, such as no explicit tool for direct cookie manipulation or DOM inspection, but the workflow tool can compensate. Overall, it is sufficiently complete for typical use cases.