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Get the scoring methodology

get_methodology
Read-onlyIdempotent

Explains how the Citehound AI readiness score is built, read from the scanner’s own check registry so it matches what runs. With no argument it returns the three pillars with their weights (they add up to 100), every check with its category, points, what it tests and why it matters, and the limits of the scan: it measures readiness and not whether any assistant names a brand; it gives half credit for a crawler with any applicable Disallow rule, usually an ordinary path; and it reads the homepage only. With a check label it returns that one check in detail. An unknown label returns an error listing the valid labels. Read-only, fetches nothing external. Use when the user asks how a score is calculated, why a check carries the points it does, or what the scan cannot tell them.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_methodology"
  }
}

Input Schema

NameRequiredDescriptionDefault
checkNoOptional. A check label exactly as scan_site reports it, e.g. "Page title" or "AI crawler access". Case does not matter. Omit for the whole methodology.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, openWorldHint=false), yet the description still contributes genuinely new behavior: the error on an unknown label that lists valid labels, the disclosure that it fetches nothing external, and the three substantive limits of the scan. That is real added context, though return structure details are only implied.

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?

Front-loaded with the purpose, then arguments, then triggers — a sensible order with no filler sentences. The dense middle clause enumerating return contents is long but every element is load-bearing given there is no output schema.

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

Completeness5/5

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

With no output schema, the description carries the burden of describing what comes back, and it does: pillar weights summing to 100, per-check category/points/rationale, plus the scan's limitations. An agent has enough to answer follow-up questions without re-invoking.

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% and the schema already documents the optional label and case-insensitivity, so the baseline is 3. The description goes further by tying labels to how scan_site reports them and specifying failure behavior for an unknown label, which meaningfully reduces invocation mistakes.

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?

States a specific resource and action — explains how the Citehound score is built — and grounds it in the scanner's own registry so the agent knows the output matches actual behavior. It is clearly separable from siblings like get_benchmark, get_playbook, or get_research, which cover other knowledge areas.

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

Usage Guidelines5/5

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

Ends with an explicit trigger list (how a score is calculated, why a check carries its points, what the scan cannot tell) and also branches on argument presence: no argument for the full methodology, a label for one check. The alternative path is spelled out rather than inferred.

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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