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Quiet Menders MCP Server

qm_validate_machine_files

Validate a site's machine-readable files by checking any URL's origin for llms.txt, agent.json, and robots.txt, and report presence and parse validity.

Instructions

Check a site's machine-readable files (llms.txt, agent.json, robots.txt) for presence and validity. Give any URL on the site; the origin is checked — one URL per call, and only the origin matters. Returns which files exist and whether each parses as valid. Free, anonymous, read-only network check. Example: url="https://brianbooms.com/lyrics/worthy" checks the brianbooms.com origin for all three files and reports presence plus validity.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesAny http(s) URL on the site to check (origin is used).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description takes on the disclosure burden and does it well: it states the operation is free, anonymous, read-only, makes a network check, and only examines the origin. It does not mention error behavior or rate limits, but the core safety profile is explicit.

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 compact and front-loaded: purpose, constraints, output, safety, and an example each earn their place. There is no filler or repetition of structured data.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter, read-only tool with no output schema, the description explains input, scope, return concept, and expected file types, plus a concrete example. Minor gaps include no exact output format, no definition of what counts as 'valid' for each file, and the possible filename typo.

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

Parameters4/5

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 meaningful semantics beyond the schema: only the origin matters regardless of path, one URL per call, and a worked example showing that a deep link still checks the site origin.

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 ('Check') and a specific resource ('a site's machine-readable files'), and enumerates three target file types with a concrete example. It is clearly distinguishable from sibling tools like qm_probe_endpoint, though the apparent typo 'lls.txt' for the standard 'llms.txt' slightly reduces precision.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear usage context: pass any site URL, only the origin is checked, and one URL per call. It does not explicitly name when not to use this tool or which sibling alternative to choose, so it stops short of full routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.