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HTTP 500 internal-error

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

C2.7/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal that only group counts are returned and that the target must be public, but it says nothing about error behavior, rate limits, network dependence, or what role the four parameters play. The 'group counts only' detail is useful but far from sufficient for a network-fetching tool.

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 carries meaning: the action, the target, the scope constraint ('public'), and the restricted output ('group counts only').

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 4 parameters, no output schema, and no annotations, yet the description never explains how the parameters relate to fetching robots.txt. Critical information is missing: what is a 'group', which parameter is required, what the return format looks like, and what happens to the json/zone inputs. This is insufficient for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, which normally earns a baseline of 3, but the schema descriptions are vague and disconnected from the tool's purpose (e.g., 'HTTPS URL to normalize or cite', 'JSON text to validate; discarded after the check', 'IANA timezone name'). The description itself adds no explanation of which parameters trigger the fetch or what json/zone have to do with robots.txt, so an agent cannot reliably construct a correct invocation.

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 ('Fetch'), a clear resource ('a public robots.txt'), and a precise return scope ('group counts only'). However, there are no sibling tool names provided to differentiate against, so it doesn't reach the level of explicit sibling 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?

The description gives no indication of when to use this tool versus alternatives, no exclusions, and no prerequisites. An agent learning whether to prefer this over a full-content-fetch tool or a search tool gets no guidance.

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

C2.4/5.0
Disambiguation2/5

citation and normalize-url both return overlapping URL metadata, http-500 overlaps with status-catalog, and timezone/utc-time/iana-zones form a fuzzy time-related cluster. compatibility is also vague about what it classifies, making tool boundaries unclear.

Naming Consistency2/5

Names are consistently hyphenated but mix noun phrases like citation, compatibility, and http-500 with verb-object forms like normalize-url, inspect-robots, and validate-json. There is no consistent naming grammar across the set.

Tool Count3/5

11 tools is a reasonable count, but the scope is unfocused: URL handling, time, HTTP status, robots.txt, and JSON validation are unrelated concerns. The number is not extreme, but the tools do not form a coherent, well-scoped set.

Completeness2/5

The set covers only isolated read-only utilities and leaves obvious gaps for a server named HTTP 500 internal-error: no actual error-diagnosis or HTTP request tools beyond status meaning/catalog, no timezone conversion, and no JSON processing beyond validation. Each micro-domain is only partially covered.