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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

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. It does add meaningful non-obvious behavior: query strings and fragments are stripped from the output. However, it stays silent on validation errors, behavior when url is omitted, and the fact that the tool accepts eight other parameters that the schema marks as discarded — the description never acknowledges the tool's broad parameter surface.

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?

Two sentences with zero filler, and the primary action is front-loaded. Both sentences carry distinct information — what is returned and what is dropped — so every word earns its place.

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?

With no output schema and no annotations, the description is lean for a tool that has nine parameters. It explains the return concept (origin, host, path) but not the output format, failure modes, or how an agent should treat the other eight parameters beyond what the schema says. It is adequate for the common case but leaves meaningful gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3, and the schema handles most parameters well with explicit 'discarded' notes. The description adds genuine meaning for the url parameter by defining what 'normalize' produces (origin, host, path) and the drop-query/fragment behavior, which goes beyond the schema's vague 'normalize or cite' phrasing.

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 names a specific verb (Return), resource (URL), and exact output components (origin, host, path), making the tool's core function unambiguous. It implicitly distinguishes itself from siblings like browser-url-ok (a validity check) and domain-shape (domain shape only) by describing component extraction rather than validation, though it never names an alternative explicitly.

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 when-to-use or when-not-to-use guidance, no prerequisites, and no mention of alternatives such as browser-url-ok, domain-shape, or web-fetch. The agent must infer that this tool is for extracting components from a URL, and the description offers no help in deciding between the many sibling tools.

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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