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Pacific/Efate clock

github-repo-shape

Parse owner and repo from a GitHub URL.

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

C2.8/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It only states 'Parse owner and repo from a GitHub URL' and does not reveal that the tool accepts and discards many other fields, what it returns, or whether it validates or extracts. The schema hints at broader behavior (e.g., 'discarded after the shape check'), but the description does not address this, leaving significant behavioral ambiguity.

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, concise sentence that front-loads the primary purpose. It has no wasted words. However, it may be too terse given the tool's apparent complexity, but for what it states, it is appropriately structured.

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?

The tool has 9 parameters and no output schema or annotations, yet the description only covers one narrow aspect (GitHub URL parsing). It does not explain the tool's broader functionality (e.g., validating JSON, checking file paths, providing weather hints), nor does it describe return values or side effects. An agent cannot fully understand how to use this tool correctly based on the description alone.

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 description coverage is 100%, so each parameter already has a clear description. The tool description adds no additional meaning beyond what the schema provides—it does not explain how the 'url' parameter relates to owner/repo parsing or clarify the purpose of the discarded fields. Since the schema handles parameter semantics adequately, a baseline score 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 clearly states the action: parse owner and repo from a GitHub URL. This is specific and distinguishes it from sibling tools like domain-shape or jira-key-shape by name and function. However, it does not mention that the schema includes many other unrelated fields (city, feed, json, etc.), which could mislead an agent about the tool's full scope.

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 such as domain-shape or file-path-ok. It does not mention prerequisites, conditions, or exclusions. An agent would have to infer usage solely 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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