MachineRead terminal-window signal markA stylized terminal window with a green signal scan-line and two data marks, indicating machine-readable signal inspection.MachineReadAI & search readiness audit

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Methodology

The 13 included check groups, three pillars, nine locked rows, and scoring formula behind the MachineRead Essentials audit.

Overview

MachineRead audits a public website URL for AI visibility, agent accessibility, scrapability, and search discovery readiness. The free Essentials audit runs 13 check groups across 3 pillars, scoring 56 checked points total.

The three pillars

Each pillar has a maximum score cap. The total is 100 points.

  • Off-site presence (cap: 30). Signals that exist outside the website itself: social and entity metadata, Wikipedia and Wikidata entity lookup.
  • AI access and scrapability (cap: 40). Signals that determine whether AI agents and crawlers can fetch, parse, and navigate the site: robots.txt AI bot policy, bot fetch access, semantic HTML, JSON-LD structured data, llms.txt, raw HTML readability, agent protocol discovery.
  • SEO (cap: 30). Signals that affect search engine indexing and discovery: crawl efficiency, canonical and HTTPS, indexing directives, search discovery hints.

The 13 check groups

Off-site pillar (cap 30):

  • Social and Entity Metadata (2 points)
  • Wikipedia and Wikidata Entity (4 points)

AI access pillar (cap 40):

  • AI Bot Policy Signals (6 points)
  • MachineRead Bot Fetch Access (6 points)
  • Semantic HTML and Agent Navigation (4 points)
  • JSON-LD Structured Data (5 points)
  • LLM Text and Markdown Access (5 points)
  • Raw HTML Readability (4 points)
  • Agent Protocol Discovery (3 points)

SEO pillar (cap 30):

  • Crawl Efficiency and HTML Performance (3 points)
  • Canonical and HTTPS (5 points)
  • Indexing Directives (5 points)
  • Search Discovery Hints (4 points)

A single check group can contain multiple underlying sub-signals. The frontend describes these as groups, not atomic checks.

Locked vs unlocked rows

The 13 check groups above are "unlocked." They are actively checked and scored.

The audit also reports 9 "locked" advanced rows in the same checks array as the 13 included rows. These are coverage gaps: the free tier acknowledges these signals matter but does not verify them. Locked rows are scored as zero, meaning the gap is visible in the total rather than hidden.

The 9 locked advanced rows

Off-site pillar:

  • Earned mentions and backlinks (Starter)
  • Owned social presence (Starter)
  • Social traction and reviews (Starter)
  • AI citation share (Pro)

AI access pillar:

  • Extraction fidelity (Starter)
  • Agent task simulation (Pro)

SEO pillar:

  • Multi-engine index coverage (Starter)
  • Core Web Vitals (Starter)
  • Keyword competitor gap (Starter)

A locked row scoring zero does not mean the underlying signal is absent. It means the free audit did not verify it.

The scoring formula

There are three separate scoring concepts:

  1. Full Rubric Score (overall_score): 100 point total. Includes locked advanced rows with score 0 until verified. Pillar caps: off-site 30, AI access 40, SEO 30.

  2. Essentials Evidence Score (benchmark.score): Computed only from included, non-locked Essentials rows. Current checked max: 56 points. Used for peer-relative benchmark comparison.

  3. Strict Agent Readiness Score (agent_readiness.score): Measures explicit agent-native discovery and protocol signals. Default scope max: 8 probes. Full scope max: 21 probes. Intended to be stricter than general crawlability or SEO.

Scope and applicability

Presets resolve applicability before checks run. The audit always returns the same 13 included rows and fixed 56-point denominator. Scope changes contextual sub-signals inside those rows, the strict agent-readiness probe maximum, exact included/excluded family copy, and benchmark cohort.

New clients should send preset and optional custom_overrides. The three legacy booleans remain for compatibility:

  • include_ecommerce: commerce schema and metadata expectations.
  • include_protocols: API and agent-protocol expectations.
  • include_account_auth: account and authorization discovery.

A selected preset wins over these booleans. Exact families prevent a site from being penalized for irrelevant commerce, account, protocol, local-business, or publisher surfaces.

Presets

The audit supports website-category presets that select check families before the scan runs:

  • Blog / Content
  • Corporate / Brand
  • Services / Local
  • News / Publisher
  • SaaS / Product / API
  • Ecommerce / Catalog
  • Custom / Power User

Custom mode lets the user add or remove supported free check families outside the default preset while keeping impossible or contradictory combinations blocked. Free preset selection is user-controlled and deterministic.

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