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Milliliters to teaspoons

domain-shape

Split a hostname into labels without WHOIS or ownership data.

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

C2.5/5.0
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 of behavioral disclosure. It does mention 'without WHOIS or ownership data,' which is a useful constraint, but it fails to explain that the tool also processes the other 8 parameters and that most are 'discarded after the check' (as the schema notes). This omission is misleading, as an agent might assume only 'host' matters.

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 sentence with no fluff, which is appropriately concise. However, its brevity comes at the cost of completeness—it omits nearly the entire parameter space. Still, for what it does say, it is well-structured and front-loaded with the core action.

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

Completeness1/5

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

This is a tool with 9 parameters, no output schema, and no annotations. The description only covers hostname splitting, ignoring the other eight parameters entirely. An agent cannot determine what inputs to provide, what the tool does with them, or what output to expect. This is critically incomplete for the tool's complexity.

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%, so the baseline is 3. The description adds no parameter meaning beyond the schema; it doesn't even reference the other parameters or clarify how they relate to the 'hostname splitting' purpose. It neither reinforces nor extends the schema descriptions, leaving the agent to rely solely on the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('split a hostname into labels') and even differentiates from WHOIS/ownership data, which separates it from some sibling shape tools. However, the tool's schema accepts 9 heterogeneous parameters (url, city, json, path, zone, etc.) that are not mentioned at all, so the description does not accurately convey the tool's full purpose. It reads like a narrow hostname-specific tool when it clearly handles many input types.

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 guidance on when to use this tool versus siblings like github-repo-shape or jira-key-shape. The description offers no context about typical use cases, prerequisites, or conditions that would select this tool over alternatives. An agent would have to infer usage from the name and description, which is insufficient.

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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