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Crawlora MCP

by net.crawlora
OverviewDiscussionsAdmin

torontostar_article

Read-only

Fetch public Toronto Star article metadata and the body paragraphs shown to anonymous readers from a canonical url. Metered articles return the public teaser, usually the first two paragraphs, with paywalled set to true. Use torontostar_headlines to find stories or torontostar_news for the general feed.

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": {
      "url": "<url>"
    },
    "name": "torontostar_article"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlYesCanonical Toronto Star article URL

Output Schema

NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / url / description
      Added value: +"Canonical Toronto Star article URL"
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Annotations only declare readOnlyHint and openWorldHint, so the description carries the meaningful behavioral burden and does so well: it warns that metered articles return only the public teaser (usually the first two paragraphs) and set `paywalled` to true. This is exactly the content-limit disclosure an agent needs before concluding an article was truncated.

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?

Three sentences, front-loaded with what is returned, then the paywall caveat, then sibling routing. Every sentence earns its place and nothing is redundant.

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

Completeness5/5

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

With an output schema present, return shape needn't be described, and the description instead covers the one thing the schema cannot: partial-body behavior for metered content. Nothing an agent needs to call this correctly is missing.

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 coverage is 100% and there is a single parameter, so the schema already documents `url`. The description adds only the word 'canonical', implying a normalized URL rather than any article page, which is a marginal but real clarification. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific verb (Fetch) and resource (Toronto Star article metadata plus body paragraphs), scoped to what anonymous readers see. An agent can distinguish it from torontostar_headlines and torontostar_news purely from the text.

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

Usage Guidelines5/5

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

Explicitly routes the agent: use torontostar_headlines to find stories, torontostar_news for the general feed, and call this when you already have a canonical article URL. The condition selecting this tool versus its siblings is spelled out, leaving nothing to inference.

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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