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Memex

Memex

by narphorium
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

analyze_web_content

Analyze web pages to extract relevant information based on a specific query. Fetches and processes content from provided URLs to answer your questions.

Instructions

Analyze multiple web pages and extract relevant information based on your query. This tool fetches and processes the content from provided URLs to answer your specific questions.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>",
      "urls": "<urls>"
    },
    "name": "analyze_web_content"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesWhat you want to learn or understand from these web pages
urlsYesA comma-separated list of web page URLs you want to analyze

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Without annotations, the description carries the full burden. It states the tool fetches and processes content, indicating read behavior, but does not disclose details like error handling, rate limits, or authentication needs. The behavioral disclosure is adequate but not rich.

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 concise with two sentences. The first sentence states the purpose, and the second adds context. It is front-loaded and efficient, though it could be slightly more structured.

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

Completeness3/5

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

The tool is simple with two parameters and no output schema. The description covers the main behavior but does not describe the return format or address edge cases like invalid URLs. It is adequate but could be more complete.

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 100%, so the baseline is 3. The description adds minimal meaning beyond the schema (e.g., 'based on your query', 'provided URLs'), but does not elaborate on parameter constraints or formats.

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 tool's action: analyze multiple web pages and extract relevant information based on a query. The verb 'analyze' and resource 'web pages' are specific, and the purpose is distinct from siblings like save_artifact and search_knowledge_base.

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 (when you have URLs and a query) but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.

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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