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Glama

AgenticTotem Web Extractor

Server Details

AI web extraction: send URLs + a JSON Schema, get clean structured data. Pay-per-use via x402.

Status
Healthy
Last Tested
Transport
Streamable HTTP
URL

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Tool DescriptionsA

Average 4.2/5 across 1 of 1 tools scored.

Server CoherenceA
Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and singular.

Naming Consistency5/5

A single tool inherently has perfect naming consistency, as there are no other tools to compare it against for patterns or conventions.

Tool Count2/5

One tool is too few for a server named 'Web Extractor' that implies broader web-related functionality. A single extraction tool feels thin and under-scoped for the domain.

Completeness2/5

The tool surface is severely incomplete for web extraction. It lacks basic operations like listing or managing extraction jobs, validating schemas, or handling errors, which are essential for a robust extraction workflow.

Available Tools

1 tool
web_extractAInspect

Extract structured data from web pages. Send 1-10 URLs and a JSON Schema describing the data shape you want. Returns extracted data for each URL. Costs $0.01 USDC per URL via x402 or MPP.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlsYesURLs to extract data from (http/https only)
schemaYesJSON Schema with type "object" and properties describing desired output shape
Behavior3/5

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

No annotations provided, so description carries full disclosure burden. It successfully reveals the cost model ($0.01 USDC, payment methods) and return behavior ('Returns extracted data for each URL'). However, it omits safety characteristics (read-only vs destructive), error handling behavior, timeout policies, and failure modes (partial vs total failure) that would be essential for a production web extraction tool.

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?

Four sentences, zero waste: (1) purpose, (2) input spec, (3) output behavior, (4) cost model. Perfectly front-loaded with the core verb. Each sentence delivers distinct, non-redundant information without reciting schema details already covered in structured fields.

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?

For a 2-parameter tool with 100% schema coverage but no annotations or output schema, the description adequately compensates by disclosing return behavior and cost structure. The mention of 'Returns extracted data for each URL' partially addresses the missing output schema, though it could specify the return format structure (array vs object) more precisely.

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?

Schema coverage is 100%, establishing baseline 3. Description adds valuable semantic context beyond the schema: specifying that the schema parameter describes 'data shape you want' (clarifying its purpose) and reinforcing the URL quantity constraints ('1-10 URLs'). Elevates understanding above raw schema definitions.

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?

Description opens with specific verb 'Extract' and clear resource 'structured data from web pages'. Immediately communicates core function without ambiguity. No siblings exist requiring differentiation, but the purpose statement is precise and actionable.

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 concrete constraints ('1-10 URLs') and critical economic context ('Costs $0.01 USDC per URL via x402 or MPP') that inform invocation decisions. Lacks explicit 'when not to use' guidance, but the cost disclosure and batch size limits effectively guide usage patterns.

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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