auditmysite

Accessibility audits for real rendered pages, built for CI and modern frontend stacks

Overview

auditmysite is a Rust CLI that audits accessibility against fully rendered pages in Chrome. Instead of scanning raw HTML only, it uses Chrome DevTools Protocol (CDP) and the browser's native Accessibility Tree, so it can evaluate dynamic DOM, computed styles, and JavaScript-heavy applications more realistically.

It is designed for teams that want a fast local check, stable JSON for automation, and a single binary that can be dropped into CI.

Why use it

• Real browser signals instead of static guesses
• Works for single pages, sitemaps, URL lists, and same-domain crawl discovery
• Outputs as terminal table, JSON, PDF, AI-optimized task list, or compact summary JSON for dashboards
• JSON output is schema-backed and tested for release stability
• Ships as a Rust binary instead of a Node-based toolchain

Why this approach

Most accessibility CLIs either depend on static parsing or require a heavier runtime stack around browser automation. auditmysite is opinionated in a different direction:

• Chrome-native accessibility data first
• CLI-first workflow for local use and CI
• Small operational surface: install a binary, point it at a URL, get a report
• Optional modules for performance, SEO, security, and mobile without changing tools

Quick Example

auditmysite https://example.com

By default, a single URL audit runs the full analysis set, prints a compact terminal summary, and writes report artifacts into the current working directory:

• ./example-com-YYYY-MM-DD-single-report.pdf
• ./example-com-YYYY-MM-DD-single-report.json
• ./example-com-YYYY-MM-DD-single-report-screen-reader-audit.json

For CI or machine-readable output:

auditmysite https://example.com -f json -o report.json --quiet

Install

curl installer (macOS/Linux)

curl -fsSL https://raw.githubusercontent.com/casoon/auditmysite/main/install.sh | bash

The installer downloads the latest GitHub Release asset for your platform and verifies it against the published .sha256 checksum before installing it.

Upgrading: run the same command again. The installer detects where your current binary lives and replaces it in place — no PATH conflicts, no leftover old version.

Note: If you previously installed via cargo install auditmysite, remove that binary first so the script installs to the right location:

rm ~/.cargo/bin/auditmysite
curl -fsSL https://raw.githubusercontent.com/casoon/auditmysite/main/install.sh | bash

Verify the installation:

auditmysite --version
auditmysite --help
auditmysite https://example.com

That default command writes report artifacts into the current directory, for example:

• ./example-com-YYYY-MM-DD-single-report.pdf
• ./example-com-YYYY-MM-DD-single-report.json
• ./example-com-YYYY-MM-DD-single-report-screen-reader-audit.json

cargo install (crates.io)

cargo install auditmysite

Requires Rust 1.75+. Builds and installs the binary from source.

Prebuilt binaries

Download from Releases.

• macOS/Linux: .tar.gz
• Windows: .zip

Build from source

git clone https://github.com/casoon/auditmysite.git
cd auditmysite
cargo build --release
./target/release/auditmysite --version

Optional Cargo features:

Feature	What it adds	Build command
pdf	PDF report generation via the renderreport/Typst engine	cargo build --release --features pdf
pdf_test	PDF rendering integration tests	cargo test --features pdf_test
semantic-eval	Fastembed local embedding for semantic link-text analysis (requires --semantic-eval flag at runtime)	cargo build --release --features semantic-eval

Requirements

• Rust 1.75+ for local builds
• Chrome, Chromium, or a managed browser install (auditmysite browser install)
• macOS, Linux, or Windows for released binaries

auditmysite requires a browser to be present at run time. It does not download or install one automatically — it reports an error and exits if none is found. To install a managed Chrome for Testing into ~/.auditmysite/browsers/:

auditmysite browser detect   # show what's found
auditmysite browser install  # download Chrome for Testing (opt-in)

Quick Start

The fastest way to validate your setup:

auditmysite https://example.com

That creates the default report set in the current directory. For machine-readable output only:

auditmysite https://example.com -f json -o report.json

Single page

# default: full audit + terminal summary + PDF/JSON in current directory
auditmysite https://example.com

# JSON
auditmysite https://example.com -f json -o report.json

# PDF with explicit path
auditmysite https://example.com -f pdf -o report.pdf

# stricter WCAG level
auditmysite https://example.com -l AAA

Batch audits

# explicit sitemap
auditmysite --sitemap https://example.com/sitemap.xml

# crawl from a base URL and discover same-domain pages automatically
auditmysite https://example.com --crawl --crawl-depth 2

# base URL: probe robots.txt / common sitemap locations first
auditmysite https://example.com

# prefer sitemap automatically if one is found
auditmysite https://example.com --prefer-sitemap

# suppress sitemap suggestion and stay on the single page
auditmysite https://example.com --no-sitemap-suggest

# URL file
auditmysite --url-file urls.txt

# per-page reports: scan a list/sitemap but write one PDF per URL instead of an aggregated batch report
auditmysite --url-file urls.txt --per-page-reports --output reports/per-page/
auditmysite --sitemap https://example.com/sitemap.xml --per-page-reports --output reports/per-page/

Browser selection

auditmysite --browser-path /path/to/chrome https://example.com

CLI

auditmysite [OPTIONS] [URL] [COMMAND]

Primary commands:

• auditmysite <url>: run a full single-page audit and write PDF/JSON into the current directory
• auditmysite --sitemap <url>: audit sitemap URLs
• auditmysite --url-file <file>: audit URLs from file
• auditmysite <url> --crawl: discover same-domain pages from a seed URL and audit them as a batch
• auditmysite browser detect: show available browsers
• auditmysite browser install: download and install Chrome for Testing into ~/.auditmysite/browsers/ (opt-in, never automatic)
• auditmysite doctor: run local diagnostics

Useful flags:

• --prefer-sitemap: if a sitemap is detected for a base URL, switch directly into batch mode
• --no-sitemap-suggest: suppress sitemap probing/suggestion and keep the run on the single URL
• --crawl-depth <n>: limit same-domain crawl discovery depth when using --crawl
• --per-page-reports: scan a URL list or sitemap but write one individual report per URL instead of an aggregated batch report; -o is treated as a target directory
• --lang <de|en>: set the language for PDF reports (default: de)
• --stack: enable tech stack detection and stack-specific security probes (included automatically with --full)
• --interactive <off|basic|full>: control the Accessibility Journey Layer for interactive checks — tab walk, skip-link, modal focus trap, SPA navigation, form-error announcement, link-text inventory (default: full; use off for fastest runs)

For the full current interface, use:

auditmysite --help
auditmysite browser --help

Output Contract

JSON output is treated as an automation contract.

• Contract documentation: docs/OUTPUT_CONTRACT.md
• Single report schema: docs/json-report.schema.json
• Batch report schema: docs/json-batch-report.schema.json

Key top-level fields in a single-page report:

• findings — static WCAG violations and SEO findings
• interactive_findings — journey-phase results (link texts, landmarks, heading outline, focus order, modal traps …); present when --interactive basic|full was used
• accessibility_journey — structured trace of each journey (steps, snapshots, durations); present when --interactive basic|full was used
• advisory_findings — semantic AI evaluation results (fastembed + Mistral); present when --semantic-eval was used; explicitly advisory, never affects score or risk

The repository validates these contracts in automated tests.

Feature Scope

WCAG rules (Level A and AA)

Core rules:

• Non-text content (1.1.1)
• Keyboard access (2.1.1)
• Bypass blocks (2.4.1)
• Language of page (3.1.1)
• Name, role, value / form labeling (4.1.2)
• Contrast minimum (1.4.3) and non-text contrast (1.4.11)
• Headings and labels (2.4.6)
• Labels or instructions (3.3.2)
• Focus order (2.4.3) and focus visible (2.4.7)
• Label in name (2.5.3)

ARIA and semantics:

• ARIA role validation — invalid roles, required owned elements, required context
• ARIA attribute checks — allowed attributes per role, required attributes, prohibited attributes
• Accessible name checks — icon-only controls, empty aria-labelledby/describedby, name/description conflicts, naming by role type (command, input, meter, progressbar, toggle, dialog, treeitem)
• ARIA relationship checks — aria-controls, aria-owns, aria-activedescendant, duplicate IDs
• Landmark structure — main, navigation, banner, contentinfo (presence, uniqueness, top-level nesting, no-duplicate for banner/contentinfo/main, required parent for landmarks)
• Content in landmarks — region rule ensuring body content lives inside landmark regions
• Table rules — caption/name, header cells, presentational tables, cell placement
• Form rules — fieldset/legend for grouped controls, required field indication, error description, label-title-only detection
• List structure — listitem context, empty lists, definition list integrity
• Dialog rules — accessible name, aria-modal, alert region labeling
• Widget rules — tab/tabpanel pairing, selected state, combobox options, slider value, tree context, summary element naming
• Media rules — application and image-role elements without accessible names
• SVG rules — SVG image accessible names
• Server-side image maps — detection and flagging
• Meta viewport — large maximum-scale restrictions

95+ rules with stable rule_id, tags (e.g. wcag2a, wcag412, cat.aria), and an impact field (critical / serious / moderate / minor).

Some criteria (keyboard trap behavior, timed content, captions) cannot be reliably verified by automated means. These are flagged as not_testable in the JSON output and listed in the report's audit scope section as requiring manual review.

AAA is not fully implemented yet.

Additional modules

Modules are classified as measured (based on real browser data) or heuristic (structural-signal estimates, marked with ~ in reports).

Measured:

• Performance: Core Web Vitals (FCP, LCP, TBT, CLS) and technical complexity (DOM size, render blocking, resource loading)
• SEO: meta tags, headings, structured data, content profile, tracking/external services signals
• Security: HTTPS, header checks, and CDN/WAF protection detection
• Mobile: viewport, touch-target, readability checks, UX heuristics (cookie-banner, modal/overlay, CTA detection)

Heuristic (indicator scores — tendency, not measurements):

• UX: 5-dimension analysis (CTA clarity, visual hierarchy, content clarity, trust signals, cognitive load) with saturation curve scoring
• Journey: user-flow analysis (entry clarity, orientation, navigation, interaction, conversion) with page-intent-aware weighting
• AI Visibility: structural readiness for LLM indexing and citation (readability, citability, structured data, AI policy, chunk quality)
• Source Quality: code hygiene signals (inline styles, deprecated elements, semantic structure, asset hygiene)
• Dark Mode: detects dark mode support via prefers-color-scheme media queries and CSS custom properties
• Tech Stack: detects CMS and frameworks (WordPress, Drupal, Joomla, Next.js, Astro, React, Vue, etc.) via in-page signals and runs stack-specific security probes (admin panel exposure, user enumeration, version disclosure)

Accessibility Journey Layer

Interactive checks run a real browser session after the static AXTree phase. They run in full mode by default and can be reduced via --interactive <off|basic|full> or mode in auditmysite.toml.

Mode	What runs
off	No interactive phase — fastest, no browser interaction after initial load
basic	Tab-walk (focus order, reverse jumps), skip-link verification, disclosure/accordion, modal focus trap, tab-list, menu journey
full (default)	Everything in basic, plus: SPA-navigation detection, form-error announcement, link-text inventory (generic/duplicate texts, heading outline, landmark structure)

Results appear in interactive_findings and accessibility_journey in the JSON output. They do not affect the accessibility score or legal_flags; critical interactive findings can raise the risk level.

auditmysite.toml configuration:

[interactive]
mode = "full"             # off | basic | full
journey_budget_ms = 8000  # wall-clock budget per URL in milliseconds (default: 6000)

Risk assessment

Risk level is computed independently from the score. A page scoring 81 can still carry "Critical" risk if it has Level A violations relevant under BFSG/EAA. Risk levels: Low, Medium, High, Critical — based on critical/high violations, legal flags, and blocking issues (4.1.2/2.1.1).

Configuration file

auditmysite.toml is an optional project-level config file placed in the working directory. It supports [audit], [rules], [interactive], [semantic_eval], [thresholds], and [budget] sections.

Security note: If you store API keys (e.g. mistral_api_key) in auditmysite.toml, add the file to .gitignore to avoid accidentally committing secrets:

echo "auditmysite.toml" >> .gitignore

Rule configuration

Rules can be selectively disabled or filtered via auditmysite.toml:

[rules]
disabled = ["heading-order", "landmark-one-main"]
# enabled_only = ["image-alt", "label"]  # run only these rules

Semantic AI evaluation

Adds a semantic layer on top of the static and interactive checks. Two providers run when --semantic-eval is set:

• Fastembed (local, no API key): embeds link texts using a multilingual model (MultilingualE5Small) and flags links that are semantically similar to known generic patterns ("Mehr erfahren", "Read more", …) — catches variations that string matching misses. Requires the semantic-eval Cargo feature: cargo build --features semantic-eval.
• Mistral (API, optional): evaluates heading-outline plausibility and produces a brief "blind user perspective" for the page. Requires a Mistral API key.

Results appear in advisory_findings in the JSON output. They are explicitly advisory — they never influence the accessibility score or risk level.

Usage:

# Fastembed only (local, no key needed)
auditmysite https://example.com --semantic-eval

# Fastembed + Mistral via environment variable
MISTRAL_API_KEY=sk-... auditmysite https://example.com --semantic-eval

auditmysite.toml configuration:

[semantic_eval]
enabled = true
mistral_model = "mistral-small-latest"   # or "open-mistral-nemo", "mistral-medium-latest"
similarity_threshold = 0.62              # fastembed cosine threshold (0.0–1.0)

# API key — omit this field and use the MISTRAL_API_KEY env var instead
# to avoid storing secrets in a file that might be committed.
# mistral_api_key = "sk-..."

Key priority: MISTRAL_API_KEY environment variable > mistral_api_key in auditmysite.toml > Mistral skipped (only Fastembed runs).

Security note: If you add mistral_api_key to auditmysite.toml, make sure the file is listed in .gitignore.

AI / LLM output format

Export findings as a task-oriented JSON list for direct LLM processing:

auditmysite https://example.com -f ai -o findings.json

Each entry is a task object with task_id, rule_id, impact, wcag, tags, title, issue, fix, selector, node_id, and help_url — sorted by impact severity. Suitable for direct use as context in AI-assisted code remediation.

Baseline and CI diff

Save a baseline snapshot and compare future runs against it:

# Save baseline
auditmysite https://example.com -f json -o baseline.json

# Future CI runs can diff against the baseline programmatically via the Rust API

The Baseline type in the audit module supports from_violations, diff, load, and save.

Report Modes

Single-page reports and sitemap/batch reports are intentionally different.

Single-page report is structured in two layers:

• Top (decision layer): hero block with score + risk level, top 3 problems, next 3 steps, overall assessment (UX/Accessibility, Technik/Sicherheit, SEO)
• Bottom (implementation layer): task block ("Was jetzt tun?" with role, effort, impact, priority), module overview, key findings, technical implementation details, detailed metrics

Sitemap/batch report is aggregated and domain-wide: averages, ranking, recurring issues, URL matrix, near-duplicate content, broken links, crawl diagnostics.

Batch reports are not a stack of single-page reports.

Compared to typical setups

• Better fit for JavaScript-heavy sites than static HTML-only checks
• Easier to distribute than a multi-package browser toolchain
• More automation-friendly than ad hoc console output because the JSON contract is explicit and tested
• Broader reporting surface than a pure accessibility-only checker when you also want performance, SEO, security, and mobile signals
• Violations carry stable rule_id, tags, and impact — easier to integrate with existing tooling or dashboards

Screen Reader Audit vs. axe-core / Pa11y

Standard accessibility checkers verify individual rules in isolation. auditmysite additionally simulates the sequential experience of a screen reader user navigating the page — detecting problems that only emerge in context.

Capability	axe-core	Pa11y	auditmysite
Rule-based WCAG checks	✓	✓	✓
Reading sequence simulation	—	—	✓
Out-of-context link text analysis (duplicate "Read more" × 8)	—	—	✓
Accessible name quality score (not just present/absent)	—	—	✓
Landmark navigation strategy (can a SR user reach main content?)	—	—	✓
BFSG / EN 301 549 legal mapping per finding	—	—	✓

When the screen reader module runs, a JSON sidecar is written automatically next to the primary report:

example-com-YYYY-MM-DD-single-report.pdf
example-com-YYYY-MM-DD-single-report-screen-reader-audit.json  ← automatic sidecar

The sidecar shows exactly what a screen reader would announce, node by node, including which announcements are ambiguous or missing — suitable as a developer reference and as evidence for BFSG compliance audits. No extra flag is required; the file is created whenever screen reader data is available in the audit result.

Typical Workflows

Examples grouped by audience and goal.

Customer-facing report (PDF)

Single-URL audit with full module coverage and a custom logo on the cover.

# default: writes a PDF + JSON sidecar to the current directory
auditmysite https://example.com --full

# explicit branding and output path
auditmysite https://example.com --full --logo ./assets/customer-logo.svg --output reports/customer.pdf

# pick a report depth: executive (management), standard (default), technical (developers)
auditmysite https://example.com --full --report-level executive --output reports/exec.pdf

# PDF language (default: de)
auditmysite https://example.com --full --lang en --output reports/report-en.pdf

CI / automation (JSON)

Quiet, machine-readable output for pipelines.

# exit code follows score thresholds; JSON report for downstream tooling
auditmysite https://example.com -f json -o report.json --quiet

# batch CI run on a sitemap
auditmysite --sitemap https://example.com/sitemap.xml -f json -o sitemap-report.json --quiet

AI fix list

Compact, agent-friendly output that focuses on actionable fixes.

auditmysite https://example.com -f ai -o fixes.json

Dashboard / ranking feed

Compact summary JSON with score, grade, medal, issue counts, and top 10 findings — matches the lastAudit schema used by dashboard tools.

auditmysite https://example.com -f summary -o summary.json

Sitemap / batch

Domain-wide audits with cross-page aggregation.

# explicit sitemap
auditmysite --sitemap https://example.com/sitemap.xml --full

# crawl from a base URL
auditmysite https://example.com --crawl --crawl-depth 2 --max-pages 50 --full

# URL list from file
auditmysite --url-file urls.txt --full

# one PDF per URL instead of an aggregated batch report
auditmysite --sitemap https://example.com/sitemap.xml --per-page-reports --output reports/per-page/

Local development

# audit a local dev server with a system Chrome
auditmysite https://localhost:3000 --browser-path /Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome

# quick CLI summary without writing files
auditmysite https://example.com --format table

Base URL with sitemap suggestion

# interactive: ask first if a sitemap is found
auditmysite https://example.com

# non-interactive: switch directly to sitemap mode
auditmysite https://example.com --prefer-sitemap

# stay on the single URL even when a sitemap exists
auditmysite https://example.com --no-sitemap-suggest

Architecture

CLI -> Browser Manager -> Chrome/CDP -> Accessibility Tree -> WCAG Engine -> Output

Key layers:

• browser/: browser detection, resolution, explicit install (browser install command only — no auto-download), lifecycle, pooling
• audit/: pipeline, normalization, scoring, batch processing
• wcag/: rule engine and violations
• output/: CLI, JSON, PDF, AI, summary format
• seo/, security/, performance/, mobile/, ux/, journey/: optional analysis modules
• tech_stack/, source_quality/, ai_visibility/, dark_mode/: heuristic indicator modules

More detail:

• Current implementation: docs/ARCHITECTURE.md
• Browser dependency details: docs/chrome-dependency.md
• Troubleshooting: docs/TROUBLESHOOTING.md

Development

Setup

git clone https://github.com/casoon/auditmysite.git
cd auditmysite
cargo test
cargo build --release
./target/release/auditmysite https://example.com

Pre-commit checks

This repository uses Git hooks with a fast local pre-commit gate and a full pre-push gate.

pre-commit runs:

• nosecrets on staged changes
• cargo fmt -- --check
• cargo clippy --lib --bins --all-features -- -D warnings

pre-push runs:

• scripts/check-version-match.sh for pushed v* tags
• cargo clippy --all-targets --all-features -- -D warnings
• cargo test

Enable the repo hook path:

git config core.hooksPath .githooks

Install nosecrets as a real binary first:

npm install -g @casoon/nosecrets
# or
cargo install nosecrets-cli

Skip the Rust checks only when you intentionally need to bypass them:

SKIP_RUST_CHECKS=1 git commit -m "..."

The hook expects nosecrets to be available in PATH.

Debugging report content (hidden --debug-typ)

PDF reports are rendered through the renderreport/Typst engine. To review report completeness and wording without opening the binary PDF, use the hidden --debug-typ flag together with --format pdf. It writes the intermediate Typst source as a .typ sidecar next to the PDF, for both single and batch reports:

# Single report → reports/example-audit.pdf + reports/example-audit.typ
./target/release/auditmysite https://example.com --full --format pdf \
  --output reports/example-audit.pdf --debug-typ

# Batch report → reports/example-batch.pdf + reports/example-batch.typ
./target/release/auditmysite --sitemap https://example.com/sitemap.xml --full \
  --format pdf --output reports/example-batch.pdf --debug-typ

The .typ file is plain text and diff-friendly — useful for checking which audits land in the report and reviewing the exact wording of every section. The flag is intentionally hidden from --help (developer/debug use only).

Release checks

Run the local release gate with:

./scripts/release-check.sh

It validates:

• cargo test
• ignored browser integration tests
• builds with and without PDF
• current --help output
• JSON contract tests
• installer/release artifact consistency
• stale docs references

Troubleshooting

• Browser not found: run auditmysite browser detect or install a managed browser with auditmysite browser install
• Running in Docker or as root: use --no-sandbox
• Need raw output for scripts: prefer -f json -o report.json
• Unsure about the full CLI surface: run auditmysite --help

Contributing

Library / Development

For library development or local work from the repository:

cargo build
cargo test

If you want the current local repository state as an installed binary while developing:

cargo install --path . --force

Contributions are welcome. At minimum before opening a PR:

cargo test
./scripts/release-check.sh

License

auditmysite is source available under the Business Source License 1.1 (BUSL-1.1). You may view, copy, modify, redistribute, and make non-production use of the source code. Limited internal production use is permitted under the Additional Use Grant in LICENSE.

Commercial SaaS rehosting, paid third-party audit services based on the Licensed Work, and use for AI training, embeddings, dataset generation, automated code ingestion, or other machine learning usage require a separate commercial license from Casoon.

Each version automatically converts to the Apache License, Version 2.0 on its Change Date. For version 0.26.0, the Change Date is 2030-05-21. Older versions released under AGPL-3.0-or-later remain under their original license terms.

Credits

• Browser automation via chromiumoxide
• PDF reports via renderreport
• WCAG reference material from W3C