Overview
MachineRead audits a public website URL for AI visibility, agent accessibility, scrapability, and search discovery readiness. The free Essentials audit runs 14 check groups across 3 pillars, scoring 60 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.
- Search (cap: 30). Signals that affect search engine indexing and discovery: crawl efficiency, canonical and HTTPS, indexing directives, search discovery hints.
The 14 check groups
Off-site pillar (cap 30):
- Social and Entity Metadata (3 points)
- Wikipedia and Wikidata Entity (3 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 (5 points)
- Agent Protocol Discovery (2 points)
- Answer Content Readiness (4 points)
Search 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.
Weights reflect impact, actionability, evidence confidence, broad applicability, and overlap. They do not count the number of probes inside a row. Important access failures and broadly useful low-effort fixes receive more weight; emerging, narrow, overlapping, or weakly inferred signals receive less.
Locked vs unlocked rows
The 14 check groups above are "unlocked." They are actively checked and scored.
The audit also reports 8 "locked" advanced rows in the same checks array as the 14 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 8 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:
- 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:
-
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, Search 30. -
Essentials Evidence Score (
benchmark.score): Computed only from included, non-locked Essentials rows. Current checked max: 60 points. Used for peer-relative benchmark comparison. -
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 Search scoring.
Scored generative source evidence
The full result also includes generative_source. This bounded HTML scan reuses
the submitted page plus up to five sitemap pages already fetched for discovery
checks. It counts sampled pages, question-led H2/H3 headings, immediate and
sourced answer passages, distinct external source links, and visible author/date
signals. It adds no request and supplies the four-point Answer Content
Readiness row in AI access.
Structured checks[].signals appear inside their scored Audit Inventory row.
Valid ARD evidence contributes to Agent Protocol Discovery. Declarative WebMCP
evidence contributes to Semantic HTML and Agent Navigation. Tool-level
limitations remain methodology caveats rather than separate inventory checks.
This evidence does not judge accuracy or originality, prove that a model retrieved or cited a page, represent every site page, verify provider traffic, or execute browser-only agent tools.
Scope and applicability
Presets resolve applicability before checks run. The audit always returns the same 14 included rows and fixed 60-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.