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America/Guatemala clock

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

B3.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose that query and fragment are dropped, which is a useful behavioral trait. However, it doesn't mention error handling for invalid URLs, whether the operation is network-based, or the format of the returned data. These gaps are notable for a tool that returns structured components.

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?

The description is a single, concise sentence that immediately conveys the core action and a key behavior (dropping query and fragment). It is front-loaded with the purpose and contains no filler or unnecessary detail.

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 description is incomplete given the tool's complexity. The schema includes nine parameters, many of which appear unrelated to URL normalization (e.g., city, zone, json), yet the description only discusses the URL. It doesn't clarify that only the 'url' parameter is used or that others are ignored. Additionally, there is no output schema, and the description doesn't specify the return format (e.g., object vs. string). This leaves an agent uncertain about how to use the tool correctly.

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?

All nine parameters have descriptions in the input schema, so schema coverage is 100%. The tool description does not add any extra meaning beyond the schema; it only mentions the URL behavior. The schema already explains each parameter, including that many are discarded after checks, so the description adds no additional semantic value.

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 clearly states the action: 'Return origin, host, and path for a URL.' It names the resource and the specific components returned, which makes the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like browser-url-ok or fetch-status, so it doesn't fully clarify when this tool is the right choice.

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 doesn't mention any conditions, exclusions, or scenarios where another tool (e.g., browser-url-ok, fetch-status) would be preferable. An agent is left to infer usage from the tool name and description alone.

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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