What to look for
- Framework defaults that survived into production
- Security and privacy gaps around app routes
- AI Search readiness and crawlable answer blocks
AI app builders
AI app launch report example with page audit fixes
See how a PageLens AI page audit helps AI app builders find SEO, security, accessibility, content and launch-readiness issues before public launch.
Likely findings
- Missing CSP and weak referrer policy
- Generic meta descriptions on feature pages
- Unclear pricing and support links
How to use the report
- Use the Markdown export to drive an agent repair loop.
- Re-scan after the first fix pass to prove score movement.
Report anatomy
A PageLens AI report is built to move from evidence to repair.
Example pages should be crawlable because the buyer needs to know what they get before starting a scan. These are the sections the Primary Scan turns into action.
Owner verdict
A plain-English launch decision before the report dives into technical findings.
Evidence snapshot
Rendered-page proof: screenshots, observed HTML, headers and the exact page affected.
Priority queue
Critical and high-risk issues first, with owner impact and acceptance criteria.
Copyable prompt
Copy-paste prompts for an AI builder, developer or agency to apply safely.
Re-scan proof
Before/after evidence after the deployed site changes.
Before / fix / after
The useful part is the proof loop.
A report should not leave you translating scanner output. It should show what failed, what to change, and what improved after the deployed page was scanned again.
Before
Missing CSP and weak referrer policy
Fix
Use the Markdown export to drive an agent repair loop.
After
Re-scan the live URL and keep the score movement, screenshot and resolved-finding proof.
Agent handoff
Use the report with the builder that created the problem.
The report is intentionally written so a founder, developer, agency or AI coding agent can act without re-diagnosing the page.
Cursor: paste the finding, route, screenshot note and acceptance criteria into the repo chat.
Codex: attach the Markdown report and ask for a scoped patch plus tests where relevant.
Lovable/Bolt: paste the priority finding and ask for the smallest safe UI or metadata fix.
Agency handoff: send the client-safe summary, then keep the detailed fix queue internal.
Start small
Use the example to choose the smallest useful scan.
If one page decides the launch, start there. If traffic will hit multiple routes, use the Launch Pack so desktop, mobile and the re-scan proof stay together.
Free Growth Baseline
$0
First visible signal
Full One-Page
$1
One URL, every finding
Launch Pack
$29
15 pages and re-scan proof
Frequently asked.
- Is this the same as a live PageLens AI report?
- It is an explainer page for a report example. The live public sample and paid reports contain the actual report UI, screenshots, findings, fix prompts and re-scan proof.
- Can I use this with Cursor, Codex, Lovable or Bolt?
- Yes. PageLens AI reports are designed to become fix prompts. Copy the finding evidence and acceptance criteria into your AI builder or coding agent, then re-scan the deployed page.
- What should I buy after reading an example report?
- Start with the Free Growth Baseline. Use the Primary Scan for one important URL, or the Launch Pack when a homepage, pricing path, social preview and mobile flow all need proof.