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xeryuscrawl

xeryuscrawl

by KingXeryus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

agent

Crawls from given URLs or web search results, finds pages matching a research goal, and answers from the best content using a configured AI model.

Instructions

Find data for a goal by browsing: from the given addresses (or a web search), crawl toward the pages that match the goal, then answer from the best of them with the configured AI model.

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": {
      "prompt": "<prompt>"
    },
    "name": "agent"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlsNo
promptYes
schemaNo
max_pagesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description must carry the full behavioral burden. It discloses the core browsing/crawling/answering flow and mentions a configured AI model, but omits operational details such as whether the operation is read-only, crawl limits beyond the unmentioned max_pages default, failure behavior, and cost or rate-limit implications.

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 a single front-loaded sentence that efficiently conveys the main workflow with no filler. It is slightly dense but well structured around the browse-crawl-answer sequence.

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?

For a tool with four parameters, no annotations, and no output schema, the description is incomplete. It provides a high-level flow but does not explain key parameters like schema and max_pages, nor does it give enough behavioral context for correct invocation in ambiguous 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?

Schema description coverage is 0%, so the description should compensate for all four parameters. It loosely explains urls ('given addresses or a web search') and prompt ('goal'), but never mentions the schema parameter or max_pages, leaving half the parameters without any semantic clarification.

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 multi-step process: find data for a goal by browsing, crawl toward matching pages from given URLs or a web search, and answer with an AI model. It is clear enough to understand the tool's core action, though the generic name 'agent' and lack of explicit contrast with siblings like deep_research or ask keep it from a 5.

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 explicit guidance on when to use this tool versus alternatives such as search, ask, scrape, crawl, or deep_research. The implied use case is goal-directed browsing, but an agent cannot determine when this is preferable to a simpler search or extraction tool.

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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