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readability_url

Analyze a URL's readability with Flesch-Kincaid and Gunning Fog scores to assess text difficulty and reading level.

Instructions

Analyze URL readability scores (Flesch-Kincaid, Gunning Fog, etc).

Parameters:
    url — The URL to analyze for readability.

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": "readability_url"
  }
}

Input Schema

Name	Required	Description	Default
`url`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.4.1Jun 22, 2026

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. It does not mention that the tool fetches the URL content, nor does it discuss edge cases (inaccessible URL, non-text content, rate limits). The description is too minimal for a tool that performs network requests.

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, front-loading the purpose and then listing the parameter. No redundant information. However, it sacrifices completeness for brevity.

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 has an output schema (not shown), so return values are already documented. However, the description does not explain that the tool fetches the URL, nor does it cover potential failure modes or prerequisites. Given the sibling set includes many readability and URL tools, more context would help disambiguate.

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?

The schema has 0% description coverage, but the description adds a brief explanation for the 'url' parameter ('The URL to analyze for readability.'). This adds some meaning beyond the schema's empty title, but lacks format requirements, examples, or constraints.

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 analyzes URL readability using specific metrics (Flesch-Kincaid, Gunning Fog). It distinguishes from siblings like 'analyze_readability' (likely for text) and 'read_url' (which likely just fetches content). The verb 'Analyze' and resource 'URL readability scores' are specific and concrete.

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?

No guidance is provided on when to use this tool versus alternatives like 'analyze_readability' or 'gunning_fog_score'. There is no mention of prerequisites (e.g., URL must be accessible) or exclusions. The agent must infer usage from context.

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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