Step 1
Run the live-site audit
Scan the public URL or preview deployment so the report captures rendered HTML, screenshots, metadata, forms, headings, links, headers, tracking and the visitor path that search engines and buyers see.
Audit-to-agent repair workflow
How to turn a website audit into Codex and Cursor fixes.
A report only helps if it becomes code, copy and configuration changes. PageLens AI gives Codex, Cursor and other AI builders a ranked repair brief with evidence, prompts and re-scan proof.
Markdown prompts for agentsBuilt for launch repair loopsRe-scan proof after deployment
Repair loop
Move from finding list to production fix.
PageLens AI is designed to preserve the context a coding agent needs: what failed, where it failed, why it matters and how to prove the repair worked after deployment.
Step 2
Export the Markdown
Use the Markdown report or copy the prioritized findings from the full report. Keep severity, evidence, screenshots, affected URLs and acceptance criteria attached to each issue.
Step 3
Paste the ranked findings into your agent
Give Codex, Cursor, Claude Code, GitHub Copilot, Windsurf or your AI builder the ranked findings first, then ask for the smallest production-safe changes that resolve them.
Step 4
Fix one risk group at a time
Start with high-impact SEO, WCAG, trust, security and conversion issues. Avoid broad redesigns until metadata, labels, headings, forms, social previews and mobile layout are stable.
Step 5
Deploy and re-scan
Ship the change to the public URL, run smoke checks, then re-scan so the report proves what improved and catches regressions introduced by the agent.
Step 6
Keep the proof with the launch record
Save the before and after reports, screenshots, prompts and deploy notes so a client, founder, marketer or reviewer can see what changed before traffic arrives.
Coding agents and AI builders
Match the report to the surface doing the repair.
The same report can feed a repository agent, an IDE assistant or the AI builder that created the page. The prompt should always carry evidence, constraints and a clear verification target.
Codex
Use when
Repo-scale changes, test runs, branch work, PRs and deploy-gate checks.
Prompt shape
Give Codex the Markdown findings, target route list, repository constraints and expected verification commands.
Open workflowCursor
Use when
IDE-level repairs across components, layouts, route metadata and copy.
Prompt shape
Paste the ranked findings into the chat, attach the relevant files and ask for scoped patches with acceptance criteria.
Open workflowClaude Code
Use when
Large-context repairs where findings touch several files or app routes.
Prompt shape
Ask it to preserve unrelated behavior, fix the audited routes first and produce a verification checklist.
Open workflowGitHub Copilot
Use when
Inline edits, small component fixes and accessibility refactors while reviewing files manually.
Prompt shape
Use one finding at a time, including the failing selector, evidence and expected visible result.
Open workflowWindsurf
Use when
Agentic edits across app code, marketing copy and generated UI flows.
Prompt shape
Group findings by route and ask for narrow diffs, then run the app locally before deployment.
Open workflowLovable, Bolt, Replit and v0
Use when
No-code or AI-builder projects where the builder needs a precise repair prompt.
Prompt shape
Paste the report evidence and ask the builder to update the deployed page, not just regenerate a prettier design.
Open workflowExample prompt
Give the agent a repair brief, not a vague instruction.
A strong prompt tells the agent what to fix, where the evidence came from, what not to touch and how the owner will verify the site is ready for launch.
- The production or preview URL that was scanned.
- The PageLens AI report link or Markdown export.
- The top high and critical findings with severity, evidence and screenshots.
- The affected routes, components or files if you already know them.
- Constraints such as no redesign, no scoring changes and no unrelated copy rewrites.
- Acceptance criteria: what should be true after the fix is deployed.
- Verification commands, browser checks and the requirement to re-scan the public URL.
Codex / Cursor prompt starter
Markdown
You are working in my codebase. I ran a PageLens AI audit on [URL].
Fix the HIGH and CRITICAL findings first. Use the evidence and affected URLs below.
Constraints:
- Keep the existing product positioning and visual design unless a finding requires a change.
- Do not change the score, severity, crawl coverage or report wording.
- Make the smallest production-safe patch that resolves each finding.
- After edits, list the files changed and verification steps.
Findings:
[paste PageLens AI Markdown findings here]Common fixes agents can make
Most launch blockers are repairable without a rebuild.
AI-built sites often need targeted production fixes, not a new design. PageLens AI keeps each finding tied to the visible issue so the agent can patch the actual page instead of guessing.
SEO and social previews
Unique titles, meta descriptions, canonicals, OG images, Twitter cards, sitemap discovery, internal links and indexable route copy.
AEO and answerability
Clear short answers, entity language, FAQs, comparison context, schema, llms.txt coverage and crawlable proof pages.
WCAG accessibility
Labels, alt text, heading order, focus states, keyboard access, contrast, error messages, tap targets and modal behavior.
Trust and conversion
Pricing clarity, contact routes, privacy links, form states, lead capture copy, support paths, proof links and CTA hierarchy.
Security and tracking
Security headers, exposed-key checks, cookie posture, analytics consent, broken third-party scripts and deploy-specific mistakes.
Mobile and launch polish
Mobile overflow, slow hero assets, layout shift, broken nav, unclear first viewport, repeated CTAs and launch-moment copy.
FAQ
Questions before sending an audit to an agent.
These answers mirror the FAQ schema so Google, answer engines and visitors see the same repair-workflow guidance.
Can Codex or Cursor fix a website audit?
Yes, if the audit includes specific evidence. Codex and Cursor can turn PageLens AI findings into code, copy and configuration changes when you provide the URL, affected routes, severity, screenshots, expected result and verification steps.
What should I paste into Codex or Cursor from a PageLens AI report?
Paste the Markdown export or prioritized findings, including severity, evidence, affected pages, screenshots, constraints and acceptance criteria. Ask the agent to fix high-risk findings first and to avoid unrelated redesigns.
Should I fix every website audit finding at once?
No. Fix one risk group at a time: metadata and crawlability, accessibility blockers, forms and conversion, trust pages, security headers, tracking and mobile layout. Smaller batches are easier to verify and less likely to regress.
How do I know the agent fixes worked?
Deploy the changes to the same public URL or preview URL, run smoke tests, then re-scan with PageLens AI. Keep the before and after report evidence so you can prove the site improved before launch traffic arrives.
Does PageLens AI work with MCP, CLI, API keys and deploy hooks?
Yes. PageLens AI has developer workflow pages for MCP, CLI, API keys, deploy hooks and GitHub Action usage so teams can pull reports into Codex, Cursor, Claude Code and other coding-agent workflows.
Get the audit, prompt pack and re-scan in one launch workflow.
Use Launch Pack when the site is about to be shared publicly, sent to a client, submitted to a directory or used for paid traffic. You get desktop and mobile evidence, agent-ready prompts and one included re-scan after the fixes are deployed.
Get the audit-to-agent repair checklist by email
We will send the prompt structure, report links and Launch Pack path for turning PageLens AI findings into Codex, Cursor and AI-builder fixes.