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Quoted-printable length, input discarded

normalize-url

Return origin, host, and path for a URL. Query and fragment are dropped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refNoGit ref name; discarded after the shape check
urlNoHTTPS URL to normalize or cite
cityNoCity name for a public weather hint; discarded after the call
feedNoPublic RSS or Atom URL; titles discarded
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
pathNoFile path to check; no disk access
zoneNoIANA timezone name
queryNoSearch text; discarded after the length check

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.1/5.0
Behavior3/5

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

The description discloses a key behavior—'Query and fragment are dropped'—which is helpful. However, with no annotations provided, it does not explain the behavior of the other eight parameters (e.g., ref, city, feed), which appear in the schema but are not mentioned in the description. This leaves uncertainty about whether they are used or ignored, reducing transparency.

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, clear sentence that front-loads the main purpose and includes the key behavioral note about dropping query and fragment. There is no wasted wording, and it is appropriately concise for the stated operation.

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?

The tool has 9 parameters and no required fields, yet the description only addresses URL normalization. It does not explain how to invoke the tool correctly (e.g., which parameter to use) or what happens when other parameters are passed. The absence of an output schema means the description should describe the return structure, but it only mentions 'origin, host, and path' without format. This is incomplete for an agent to use reliably.

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 input schema has 100% description coverage, so every parameter is already documented with its purpose (e.g., 'url: HTTPS URL to normalize or cite'). The tool description adds minimal value beyond stating the output; it does not clarify how parameters map to the URL normalization logic or which parameter is primary. With high schema coverage, a baseline of 3 is appropriate.

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 clear verb and resource: 'Return origin, host, and path for a URL.' This is specific and immediately understandable. However, it does not differentiate from sibling tools like domain-shape or github-repo-shape, which also handle URL-related shapes, so it lacks explicit distinction.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any sibling tools or conditions for selecting normalize-url over domain-shape, github-repo-shape, or similar. An agent is left to infer usage solely from the description.

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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