Atlas SEO Audit Console

Crawl-based audit system for search.

Atlas is a technical SEO audit system that crawls, interprets, and scores websites to surface what search engines see across architecture, indexation, and performance. It is not a generic content-writing product.

Beyond Basic Crawls

Atlas goes deeper than surface reports. It interprets signals, correlates patterns, and prioritizes issues by impact on indexation and visibility.

Search Visibility Aware

Atlas evaluates content and structure for entity clarity, source signals, freshness, and crawlability.

Built for Operators

Designed for SEO operators and technical teams who need reliable source material, clear logic, and inspectable outputs to drive decisions.

The Atlas Process

Crawl

High-fidelity crawling with smart rate control, JavaScript rendering, and adaptive discovery to map the site as search engines do.

Extract

Extract content, links, directives, structured data, signals, and performance data from every discovered URL.

Interpret

Normalize and connect signals into an understanding of architecture, intent, and indexation potential.

Score

Score issues by severity, confidence, affected URLs, implementation effort, and source quality using documented audit rules.

Report

Structure operator-ready reports, preview packages, and task lists with source notes and recommended actions.

What Atlas SEO Audit Console Checks

URL discovery

Atlas starts from discovered URLs and crawl records, not only manual page samples.

robots.txt

Robots directives are part of the audit evidence used to understand crawler access.

XML sitemaps

Sitemaps are checked as route and freshness signals rather than assumed to be complete.

raw HTML

Raw source evidence helps compare what a crawler receives before client-side rendering.

rendered HTML

Rendered-page checks help separate source HTML from browser-visible content and links.

titles/meta

Document titles and meta descriptions are treated as inspectable page-level evidence.

canonicals

Canonical URLs are checked for duplicate-path, consolidation, and indexation clarity.

structured data

JSON-LD and visible page text are aligned so entity claims are structured and readable.

internal links

Internal link evidence supports crawl-depth, orphan-risk, and page-relationship analysis.

scoring

Findings are prioritized by severity, confidence, affected URLs, effort, and evidence quality.

SQLite persistence

Crawl records can be persisted for repeatable review instead of treated as one-off notes.

exports/dashboards

Audit outputs are structured for operators and client-facing review, with evidence attached to recommendations.

Data and Outputs

Structured outputs make crawler observations reviewable, inspectable, and defensible across technical teams.

Issue Detection

Prioritized technical issues with impact scoring, severity labels, crawler observations, and remediation steps.

Internal Link Graph

A map of flow, crawl depth, orphan risk, inlinks, outlinks, and authority distribution across important pages.

Indexation Overview

Crawlable versus indexable status across valid sitemap entries, noindex headers, canonical gaps, and robots-blocked URLs.

Technical Findings

Examples with affected URLs, confidence, source notes, and next implementation actions.

Export Preview

Sample executive summaries, technical audit sections, issue tables, crawl data layouts, and dashboard views for operators.

Capability Status

Crawl inventory — Shipped

Public sanitized run available.

Evidence ledger — Shipped

Observed and interpreted states remain separate.

Run persistence and exports — Shipped / partial

Technical architecture is documented; public coverage remains bounded.

Provider mesh — Prototype

Missing provider coverage remains a measurement gap.

Scoring policy — In development

The review gate remains authoritative.

Specific Data Handled by Atlas

Atlas evidence

Technical SEO evidence

Finance research evidence

Source Links

System Intelligence You Can Act On

Atlas turns complexity into inspectable records so operators can decide what matters, what should be fixed, and what source data supports the recommendation.

Internal Links