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Glama

UUID shape check

inspect-robots

Fetch a public robots.txt and return group counts only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoHTTPS URL to normalize or cite
hostNoPublic hostname
jsonNoJSON text to validate; discarded after the check
zoneNoIANA timezone name

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose a meaningful behavioral trait — output is summarized to group counts only, not full file contents. However, it omits other relevant behaviors such as network failure handling, redirects, non-robots content, and what 'groups' means, leaving the agent without a complete safety/behavior picture.

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?

A single front-loaded sentence with zero filler. Every word earns its place, and the core operation is stated before any constraints.

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 4 parameters, no required parameters, no output schema, and no annotations, the one-sentence description is insufficient. It never says which parameter supplies the robots.txt URL, what 'group counts' look like in the response, or how to handle the seemingly unrelated json/zone parameters. An agent cannot reliably invoke this tool from 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 the baseline is 3; every parameter has its own description and the tool description adds no additional parameter meaning. In fact, the 'url' parameter description ('HTTPS URL to normalize or cite') conflicts with the described robots.txt fetching purpose, which the description does nothing to resolve.

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 names a specific verb ('Fetch'), resource ('a public robots.txt'), and output constraint ('return group counts only'), so an agent can tell what the tool is for. It loses a point because the input schema's parameters describe URL normalization, JSON validation, and timezone handling, which do not obviously align with fetching robots.txt, muddying the stated 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?

There is no guidance on when to use this tool versus alternatives, no stated preconditions (e.g., robots.txt must exist, site must be public), and no exclusions. The single sentence implies the use case but never explains under what circumstances an agent should pick this tool.

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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TDQS

C2.6/5.0
Disambiguation3/5

A few clusters overlap—citation and normalize-url both analyze URLs, and timezone and utc-time both provide current time—but the descriptions generally make the intended output clear. The vague 'compatibility' tool adds some ambiguity, but no tools are truly indistinguishable.

Naming Consistency3/5

All names use lowercase hyphenation, but the naming pattern is mixed: some are verb-noun (inspect-robots, normalize-url, validate-json), while others are noun compounds (domain-shape, status-catalog) or single nouns (citation, timezone). This is readable but not predictably consistent.

Tool Count4/5

11 tools is within the reasonable 3-15 range and each tool has a distinct purpose. However, the set spans URL inspection, time, UUID, JSON, and HTTP status, so it feels slightly broader than the server name implies.

Completeness4/5

For a shape and inspection utility server, the main categories are covered: URL normalization, robots.txt inspection, HTTP status, timezone lookup, current time, JSON validation, and UUID shape checking. Minor gaps exist like redirect chains or JSON schema validation, but the core surface is not severely incomplete.