Analyze a web page for screen-reader navigation cost. Returns scored findings showing how hard it is for AT users to discover, reach, and operate interactive targets. Navigates to the URL in a sandboxed browser. Probes test keyboard behavior but do not submit forms or modify data.

Recommended: Use format='sarif' for concise, actionable output (~4KB). SARIF auto-filters to findings that need attention (moderate and worse). JSON/markdown include every target and can be 100x larger.

SPAs (React, Next.js, etc.): Pass waitForSelector (e.g., '[data-testid="app"]' or 'main') so Tactual waits for the app to hydrate before capturing.

Validate Tactual's predicted navigation paths against a virtual screen reader. Runs analyze_url internally, then for each worst finding drives @guidepup/virtual-screen-reader over the captured DOM (via jsdom) to check: (a) is the target reachable at all, and (b) how many virtual SR announcements does it take to reach it? Compares to Tactual's predicted step count. Returns an accuracy ratio per target and a mean across all validated targets — closer to 1.0 means Tactual's predictions match this virtual-screen-reader run, not a guarantee of full real-AT fidelity.

Requires (optional deps): jsdom + @guidepup/virtual-screen-reader. Installed with tactual if optionalDependencies were honored; otherwise run npm install jsdom @guidepup/virtual-screen-reader in your project.

When to use: closing the predicted-vs-actual loop. If Tactual's predictions diverge a lot from the virtual SR, either the profile weights need calibration or the page has structural patterns the analyzer doesn't model. Use sparingly — this adds the analyze_url cost plus jsdom parsing + virtual SR navigation time.

List the assistive-technology (AT) profiles available for scoring. Each profile models a specific screen reader and platform — e.g., NVDA on Windows, VoiceOver on iOS — with its own navigation cost weights and action vocabulary. Returns an array of {id, name, platform, description} for each profile.

Read-only, no parameters, static data. Call once to discover valid profile IDs, then pass a profile ID to analyze_url, trace_path, or analyze_pages. Default profile for all analysis tools is 'generic-mobile-web-sr-v0' if none is specified.

Compare two Tactual analysis results (before/after). Shows what improved, regressed, which penalties were resolved or added, and severity band changes per target. Returns a JSON array of {targetId, baselineScore, candidateScore, status, penalties}.

Read-only, no side effects. Use after fixing accessibility issues to verify improvements. Both inputs must be JSON strings from analyze_url (format='json'). Not useful for SARIF output — use analyze_url directly for before/after SARIF comparisons.

Extract the top unique remediation suggestions from a Tactual analysis result, ranked by severity. Returns a JSON array of {targetId, severity, score, fix, penalties}.

Read-only, no side effects. Most useful with large JSON results where you want a prioritized shortlist of what to fix first. For SARIF results, the findings already contain fix suggestions inline — this tool is redundant in that case. Input must be a JSON string from analyze_url (format='json').

Trace the exact screen-reader navigation path to a specific interactive target. Returns step-by-step actions a screen-reader user would perform, with modeled announcements, cumulative cost, and the target's role/name at each hop. Read-only — navigates to the URL but does not modify the page.

Use this after analyze_url to understand why a target scored poorly.

For auth-gated or explored targets: Pass statesJson from a prior analyze_url (use includeStates=true). This skips browser launch entirely and traces against the captured state, including any explored states discovered behind auth boundaries.

Authenticate with a web application and save the session for subsequent analysis. Navigates to the URL, executes login steps (click a button, fill a form, etc.), waits for the authenticated page to load, then saves cookies and localStorage to a JSON file. Overwrites the output file if it already exists.

Side effects: Writes a storageState JSON file to disk at outputPath. Launches a headed browser that interacts with the page (clicks, fills inputs). Not needed for public pages — only use when content is behind authentication.

Pass the output file path as storageState to analyze_url, trace_path, or analyze_pages to analyze authenticated content.

Steps format: Array of actions to perform in order. Each step is an object:

• { click: 'button text or selector' } — click a button/link

• { fill: ['input selector', 'value'] } — fill an input field

• { wait: 2000 } — wait N milliseconds

• { waitForUrl: '/dashboard' } — wait until URL contains this string

Example for a dev login: steps: [{ click: 'Dev Login' }, { waitForUrl: '/workspace' }] Example for form login: steps: [{ fill: ['#email', 'user@test.com'] }, { fill: ['#password', 'pass'] }, { click: 'Sign In' }, { waitForUrl: '/dashboard' }]

Analyze multiple pages and produce an aggregated site-level report. Runs analyze_url on each URL in a single browser session and combines results into a site score with per-page breakdown. Read-only — navigates to each URL but does not modify pages.

Use this instead of calling analyze_url repeatedly when you need a site-level assessment. Returns ~200 bytes per page plus a site-level summary. If a single URL fails (timeout, bot protection), its entry shows the error and remaining URLs still complete.