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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

B3.1/5.0
Behavior2/5

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

No annotations are provided, so the description bears the full burden of behavioral disclosure. It only says 'Parse' and does not mention return format, validation/error behavior for non-GitHub URLs, or whether the unrelated schema fields (city, feed, json, path, query) are ignored. The schema hints at discarding inputs, but the description itself leaves side effects and output behavior opaque.

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, front-loaded sentence with no wasted words. However, it is quite terse given the 9-parameter schema and could carry more useful context without becoming verbose.

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?

With nine optional parameters, no annotations, and no output schema, the description is under-specified. It does not explain what the parsed owner/repo looks like, what happens for invalid URLs, or how the many unrelated schema fields relate to this tool. An agent would need to infer or experiment to use it reliably.

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 even though the description adds no per-parameter detail. The description does clarify that the relevant input is a GitHub URL, which helps disambiguate the generic 'url' schema description, but it never names which of the nine optional parameters should be populated or acknowledges that the other parameters appear irrelevant. This is adequate but not exemplary.

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

Purpose5/5

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

The description uses a specific verb ('Parse') and a specific resource ('owner and repo from a GitHub URL'), making the tool's core function immediately identifiable. It also distinguishes this from sibling shape tools like domain-shape and jira-key-shape by naming GitHub and the extracted fields. No ambiguity about the high-level purpose.

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 gives no guidance on when to choose this tool over alternatives such as normalize-url, browser-url-ok, or the other *-shape tools. It does not state that it is limited to GitHub URLs or that other URL-related tasks should use a sibling. Usage is only implied by the tool name and the one-line description.

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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