🔧 ADA Website Fix-It Report

Turn accessibility scan results into developer-ready remediation reports. Every violation gets a plain-English explanation, AI-generated code fix, cost estimate, and recommended fix-by timeline. Includes competitor benchmarking and markdown export — everything agencies need to sell remediation and developers need to execute fixes.

📋 Table of Contents

• What is this?
• How to use
• Input
• Output
• JSON output example
• How much does it cost?
• Use cases
• Integrations
• Is it legal?
• Troubleshooting
• FAQ
• Tech stack
• Feedback & issues

🤔 What is this?

ADA Website Fix-It Report takes raw accessibility scan data and transforms it into actionable, developer-ready remediation documentation. Instead of handing developers a list of rule IDs, this Actor translates each violation into plain English ("Text is too hard to read against its background color"), generates a working code snippet to fix it, estimates labor hours and dollar costs, and sets a recommended fix-by timeline based on severity.

It also scans competitor websites and includes a benchmark comparison in the report — so agencies can show prospects exactly where they stand vs their competitors. Output in JSON, markdown, or both.

Perfect for: agencies pitching remediation services, dev teams receiving actionable fix tickets, and compliance officers documenting remediation timelines.

🚀 How to use

Step 1: Provide URLs or scan results

You have two options:

Option A — Scan + Report (all-in-one):

{
  "startUrls": [{ "url": "https://example.com" }]
}

The Actor scans each URL with axe-core, then generates the full remediation report.

Option B — Report from existing scan:

{
  "scanResult": [<dataset items from ADA Scanner Actor>]
}

Skip re-scanning by feeding results from our companion Actor: ADA Website Compliance Checker.

Step 2: Add competitors (optional)

{
  "startUrls": [{ "url": "https://yoursite.com" }],
  "competitorUrls": [
    { "url": "https://competitor1.com" },
    { "url": "https://competitor2.com" }
  ]
}

The Actor scans competitor sites and includes a benchmark comparison table in the report.

Step 3: Choose output format

reportFormat	Output
json	Structured JSON in dataset + key-value store (default)
markdown	Human-readable markdown report in key-value store
both	JSON + markdown

Step 4: Run + export

Click Start. Results appear in:

• Dataset — Per-page remediation items (push individually)
• Key-value store — OUTPUT key with aggregated report + markdown

Quick start (API)

{
  "startUrls": [{ "url": "https://example.com" }],
  "competitorUrls": [{ "url": "https://competitor.com" }],
  "reportFormat": "both"
}

📥 Input

Field	Type	Default	Description
startUrls	array	—	URLs to scan + report. Format: [{ "url": "https://..." }]
scanResult	array	—	Pre-existing scan results JSON (from Scanner Actor). Skips re-scanning.
competitorUrls	array	—	Optional competitor URLs for benchmark comparison
reportFormat	string	json	Output format: json, markdown, or both
llmModel	string	auto	LLM model for code snippet generation

Note: Provide either startUrls or scanResult — not both. If scanResult is provided, the Actor skips scanning and goes straight to report generation.

📤 Output

Per-page remediation (dataset)

Each scanned page produces a remediation report pushed to the dataset:

Field	Type	Description
url	string	Page URL
pageTitle	string	Page title
scanDate	string	ISO 8601 scan timestamp
remediationSummary	object	Total cost (low/high), hours, violations by severity, grade, risk, fix-by date
remediationItems	array	Each violation with plain English, code snippet, cost, hours, help URL
itemsByPriority	object	Items grouped: critical, serious, moderate, minor

Per-violation item

Field	Type	Description
ruleId	string	axe-core rule ID (e.g., color-contrast)
impact	string	Severity: critical, serious, moderate, minor
plainEnglish	string	Human-readable description (e.g., "Text is too hard to read against its background color")
technicalDescription	string	axe-core's technical description
affectedElements	integer	Number of elements affected
codeSnippet	string	AI-generated code fix (HTML/CSS)
costLow	number	Estimated cost — low end (USD)
costHigh	number	Estimated cost — high end (USD)
estimatedHours	number	Estimated labor hours
helpUrl	string	Link to Deque's remediation guide
examples	array	Up to 3 affected elements with CSS selector, HTML snippet, failure summary

Aggregated output (key-value store)

Field	Type	Description
reportDate	string	Report generation timestamp
totalPages	integer	Pages scanned
totalCostLow	number	Total estimated cost — low end
totalCostHigh	number	Total estimated cost — high end
totalHours	number	Total estimated labor hours
overallGrade	string	Overall compliance grade (A–F)
overallRisk	string	Overall lawsuit risk level
recommendedFixBy	string	Date by which critical issues should be addressed
reports	array	Per-page remediation reports
competitors	array	Competitor benchmark results (if provided)
markdownReport	string	Full markdown report (if reportFormat includes markdown)

📄 JSON output example

Here's real output from scanning example.com (clean site) and a fictional broken site:

Clean site result

{
  "url": "https://example.com",
  "pageTitle": "Example Domain",
  "scanDate": "2026-07-04T02:15:33.841Z",
  "remediationSummary": {
    "totalCostLow": 0,
    "totalCostHigh": 0,
    "totalHours": 0,
    "criticalCount": 0,
    "seriousCount": 0,
    "moderateCount": 0,
    "minorCount": 0,
    "recommendedFixBy": "2026-10-02",
    "grade": "A",
    "lawsuitRisk": "Low",
    "complianceScore": 100
  },
  "remediationItems": [],
  "itemsByPriority": {
    "critical": [],
    "serious": [],
    "moderate": [],
    "minor": []
  }
}

Site with violations

{
  "url": "https://broken-site.example",
  "pageTitle": "ACME Corp — Home",
  "scanDate": "2026-07-04T02:20:15.123Z",
  "remediationSummary": {
    "totalCostLow": 88,
    "totalCostHigh": 185,
    "totalHours": 2.8,
    "criticalCount": 1,
    "seriousCount": 2,
    "moderateCount": 1,
    "minorCount": 0,
    "recommendedFixBy": "2026-07-18",
    "grade": "D",
    "lawsuitRisk": "High",
    "complianceScore": 62
  },
  "remediationItems": [
    {
      "ruleId": "html-has-lang",
      "impact": "serious",
      "plainEnglish": "Page is missing language declaration (needed for screen readers)",
      "technicalDescription": "Ensures every HTML document has a lang attribute",
      "affectedElements": 1,
      "codeSnippet": "<html lang=\"en\">",
      "costLow": 5,
      "costHigh": 10,
      "estimatedHours": 0.1,
      "helpUrl": "https://dequeuniversity.com/rules/axe/html-has-lang",
      "examples": [
        {
          "target": ["html"],
          "html": "<html>",
          "failureSummary": "Fix any of the following:\n  The <html> element does not have a lang attribute"
        }
      ]
    },
    {
      "ruleId": "image-alt",
      "impact": "critical",
      "plainEnglish": "Images are missing text descriptions for screen reader users",
      "technicalDescription": "Ensures <img> elements have alternate text or a role of none or presentation",
      "affectedElements": 2,
      "codeSnippet": "<!-- Add alt text to images -->\n<img src=\"/logo.png\" alt=\"ACME Corp logo\">",
      "costLow": 16,
      "costHigh": 30,
      "estimatedHours": 0.4,
      "helpUrl": "https://dequeuniversity.com/rules/axe/image-alt",
      "examples": [
        {
          "target": ["img.hero-logo"],
          "html": "<img src=\"/logo.png\" class=\"hero-logo\">",
          "failureSummary": "Fix any of the following:\n  Element does not have an alt attribute"
        }
      ]
    },
    {
      "ruleId": "color-contrast",
      "impact": "serious",
      "plainEnglish": "Text is too hard to read against its background color",
      "technicalDescription": "Ensures the contrast between foreground and background colors meets WCAG 2 AA contrast ratio thresholds",
      "affectedElements": 1,
      "codeSnippet": "/* Increase contrast: minimum 4.5:1 for normal text */\n.cta-button {\n  color: #595959 !important;\n}",
      "costLow": 15,
      "costHigh": 30,
      "estimatedHours": 0.5,
      "helpUrl": "https://dequeuniversity.com/rules/axe/color-contrast",
      "examples": [
        {
          "target": [".cta-button"],
          "html": "<a href=\"/contact\" class=\"cta-button\">Contact Us</a>",
          "failureSummary": "Fix any of the following:\n  Element has insufficient color contrast of 2.8:1"
        }
      ]
    },
    {
      "ruleId": "label",
      "impact": "moderate",
      "plainEnglish": "Form fields are missing descriptive labels",
      "technicalDescription": "Ensures every form element has a label",
      "affectedElements": 1,
      "codeSnippet": "<label for=\"input-id\">Field label</label>\n<input id=\"input-id\" type=\"text\" name=\"field\">",
      "costLow": 20,
      "costHigh": 40,
      "estimatedHours": 0.5,
      "helpUrl": "https://dequeuniversity.com/rules/axe/label",
      "examples": [
        {
          "target": ["#newsletter-email"],
          "html": "<input type=\"email\" id=\"newsletter-email\" placeholder=\"Email\">",
          "failureSummary": "Fix any of the following:\n  Form element does not have an explicit label"
        }
      ]
    }
  ],
  "itemsByPriority": {
    "critical": [{ "ruleId": "image-alt", "..." : "..." }],
    "serious": [
      { "ruleId": "html-has-lang", "..." : "..." },
      { "ruleId": "color-contrast", "..." : "..." }
    ],
    "moderate": [{ "ruleId": "label", "..." : "..." }],
    "minor": []
  }
}

Competitor benchmark (when competitorUrls provided)

{
  "competitors": [
    {
      "url": "https://competitor1.com",
      "pageTitle": "Competitor 1 — Home",
      "score": 85,
      "grade": "B",
      "risk": "Low",
      "totalViolations": 2,
      "critical": 0,
      "serious": 1
    },
    {
      "url": "https://competitor2.com",
      "pageTitle": "Competitor 2 — Home",
      "score": 45,
      "grade": "F",
      "risk": "High",
      "totalViolations": 8,
      "critical": 2,
      "serious": 3
    }
  ]
}

💰 How much does it cost?

$5 per page report. Includes axe-core scan + AI-generated code snippets + cost estimation + competitor benchmarking. No subscription needed.

Cost examples

Use case	Pages	Competitors	Cost
Single page report	1	0	$5
Full page report + 2 competitors	1	2	$5 (competitor scans included)
5-page website audit	5	0	$25
Agency pitch (prospect + 3 competitors)	1	3	$5
Client portfolio (10 sites × 1 page)	10	0	$50
Full website remediation plan (20 pages)	20	0	$100

Money-saving tip: Run our free ADA Scanner first to identify sites with violations. Only run this report on sites that need remediation. Feed scanner results via scanResult input to skip re-scanning and save on compute.

🎯 Use cases

• Agency pitch tool — Scan prospect site, generate report showing violations + cost + fix timeline. Hands the prospect a ready-made remediation proposal
• Developer handoff — Code snippets + cost estimates give developers everything needed to start fixing. No guessing what "accessible" means
• Compliance documentation — Generate reports with fix-by dates for legal teams, insurance, and audit trails
• Portfolio scoring — Bulk scan client sites, rank by compliance score, prioritize remediation budget
• Competitive analysis — Show prospects where they rank vs competitors on accessibility. "Your site is Grade D, your competitor is Grade B — here's what they're doing right"
• Pre-litigation assessment — Document known violations + remediation timeline. Shows good-faith compliance efforts

🔗 Integrations

Chain with ADA Scanner

Feed scanner results directly into this Actor to skip re-scanning:

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")

# Step 1: Scan
scan_run = client.actor("upstanding_biobot/ada-wcag-compliance-scan").call(run_input={
    "startUrls": [{"url": "https://example.com"}]
})
scan_results = client.dataset(scan_run["defaultDatasetId"]).list_items().items

# Step 2: Generate report (no re-scan needed)
report_run = client.actor("upstanding_biobot/ada-remediation-report").call(run_input={
    "scanResult": scan_results,
    "reportFormat": "both"
})
report = client.key_value_store(report_run["defaultKeyValueStoreId"]).get_record("OUTPUT")

AI agents (MCP)

Both Actors work with the Apify MCP server (https://mcp.apify.com). AI agents can chain scanner → report autonomously:

User: "Check example.com for accessibility issues and give me a fix plan"
Agent: [runs scanner] → [feeds results to report Actor] → [returns markdown report]

Automation platforms

• Zapier — New scan result → trigger report Actor → email PDF to client
• Make (Integromat) — Schedule weekly accessibility monitoring → generate report → post to Slack
• Custom webhooks — Apify webhooks trigger downstream processing on report completion
• LangChain/LlamaIndex — Feed report data to LLMs for automated fix prioritization

⚖️ Is it legal?

Yes. This Actor performs automated accessibility scans on public web pages and generates reports based on those scans. It uses axe-core (open-source, MPL 2.0) — the same engine used by accessibility auditors worldwide.

• What it does: Loads public web pages, runs WCAG rules, generates remediation guidance
• What it doesn't do: It does not modify, hack, or breach any website
• ADA context: ADA Title III lawsuits related to website accessibility have surged — over 4,500 filed in 2023 alone. Automated accessibility testing is a recognized best practice for documenting compliance efforts. Having scan results + remediation timeline demonstrates good-faith effort
• Cost estimates: Labor hours and dollar ranges are based on industry averages for front-end developer work. Actual costs vary by developer, region, and project complexity
• Not legal advice: This report does not constitute legal advice or guarantee legal compliance. Consult an ADA attorney for legal assessment

🔧 Troubleshooting

Problem	Cause	Fix
Empty report (0 items)	Site had no violations, or scan found nothing	Check the remediationSummary.grade — if it's "A", the site is clean. If "F" with 0 items, the page didn't render
"No startUrls or scanResult" error	Neither input provided	Provide either startUrls or scanResult (from the Scanner Actor)
Code snippets look generic	LLM endpoint not configured or unreachable	Actor falls back to template snippets when LLM is unavailable. Check llmModel setting
Competitor scan timeout	Competitor site slow or blocking	Remove problematic competitor URL or try again
Markdown report missing	reportFormat not set to markdown or both	Set reportFormat: "both" to get JSON + markdown
Duplicate violations scanned twice	Provided both startUrls and scanResult	Use one or the other. If both provided, scanResult takes priority

❓ FAQ

🛠️ Tech stack

• axe-core — Deque's WCAG testing engine (90+ rules)
• Playwright — Headless Chromium browser automation
• AI code generation — LLM-powered code snippet generation for remediation
• Apify SDK — Platform integration, dataset, key-value store

🔧 Companion Actors

Complete your audit pipeline with these related tools:

Actor	What it does	Price
Website Health Check	9-in-1 audit: accessibility + security + SSL + broken links + SEO + performance	$3/URL
ADA Compliance Checker	Scan any website for WCAG violations. Feed results to this Actor via scanResult	$2/scan
llms.txt Generator	Generate llms.txt + check AI bot access. Boost AI search visibility	FREE
AI Citation Monitor	Track brand mentions in AI search responses	$0.50/query

Recommended workflow

1. Health Check — Run broad 9-check audit first ($3/URL)
2. ADA Scanner — Deep-dive accessibility violations ($2/scan)
3. ADA Fix-It Report (this Actor) — Generate developer-ready remediation plan ($5/page)
4. llms.txt Generator — Ensure AI search engines can find your site (FREE)
5. AI Citation Monitor — Track whether AI models mention your brand ($0.50/query)

💬 Feedback & issues

Found a bug? Have a feature request? Want better cost estimates for your region?

• Apify Console — Use the Issues tab on this Actor's page
• Review — Leave a rating/review on the Actor's Store page
• Direct — We monitor all feedback through the Apify platform

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This Actor is not affiliated with Deque Systems. axe-core is an open-source project licensed under MPL 2.0. Cost estimates are based on industry averages and are not guaranteed.