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KSUID character length

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?

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only says 'Parse owner and repo from a GitHub URL' and does not explain what happens with the other parameters, what the output format is, whether it validates or normalizes input, or any side effects. The schema includes 'discarded' notes for several parameters, but the description omits any behavioral detail about them.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence with no waste. However, it is under-specified for a tool with nine optional parameters and a specific extraction task. It is concise but lacks critical detail, so it does not fully earn a higher score.

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?

Given the complexity of the tool (9 parameters, no output schema, no annotations), the description is incomplete. It does not explain the role of the majority of parameters (city, feed, host, json, path, zone, query) or how they interact with the parsing logic. An agent cannot determine how to correctly invoke the tool for its stated purpose without additional information.

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 schema descriptions cover 100% of parameters, each with explicit descriptions (e.g., 'Git ref name; discarded after the shape check'). The description adds no additional semantics about how these parameters relate to parsing owner/repo. Since the schema already documents each parameter, the description does not need to repeat that, but it also fails to clarify the purpose of the unrelated parameters in the context of the stated goal. Baseline 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 specific verb and resource: 'Parse owner and repo from a GitHub URL.' This clearly distinguishes the tool's core intent. However, the input schema includes nine unrelated parameters (city, feed, host, json, path, zone, query) that are not mentioned in the description, creating ambiguity about the tool's full scope. The core purpose is clear, but the mismatch prevents a 5.

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 its siblings like normalize-url, browser-url-ok, or domain-shape. The description does not mention alternatives, prerequisites, or typical use cases. An agent would have to infer usage from the name 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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