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TOML table count, body discarded

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

C2.9/5.0
Behavior2/5

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

With no annotations provided, the description bears the full burden of behavioral disclosure. It fails to mention that only the 'url' parameter is used and the other eight are discarded, nor does it explain the return format, error handling, or what happens for non-GitHub URLs. This is a significant gap for a tool that appears to ignore most of its schema.

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?

The description is a single, focused sentence with no filler. It is appropriately front-loaded and every word earns its place, making it highly concise and easy to parse.

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?

The tool has 9 parameters, all optional, but the description only explains one. There is no output schema, so the agent cannot infer what the tool returns. The description is far too thin for a tool with such a complex and seemingly mismatched schema, leaving the agent to guess about the other parameters and expected behavior.

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 meaning to the 'url' parameter by implying it should be a GitHub URL, but it does not clarify the purpose of the other eight parameters (city, feed, host, etc.), which are clearly irrelevant to the stated task. This partial clarification keeps it at baseline.

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 ('Parse') and resource ('owner and repo from a GitHub URL'), making the core action clear. However, it does not differentiate from sibling URL-handling tools like 'normalize-url' or 'browser-url-ok', which also deal with URLs, so it loses a point for lack of explicit distinction.

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?

No guidance is provided on when to use this tool versus alternatives such as 'normalize-url' or other shape tools. The description simply states what it does without any context on selection criteria, prerequisites, or situations where it should not be used.

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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