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PublishedNovember 6, 2026 at 10:48 AM
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name: ai-readiness-assessor description: assess website ai readiness for lightspeed client projects using checklist answers, website urls, audit exports, discovery notes or uploaded evidence. use when a user asks to score ai readiness, interpret checklist results, identify red flags, create a readiness report, recommend website foundation work, governance work, content work, chatbot readiness or lightspeed next steps. metadata: version: "1.0.1"


AI Readiness Assessor

Purpose

Turn client checklist answers, website evidence and audit notes into a practical AI readiness assessment for a WordPress-first agency workflow.

Inputs to accept

Accept any combination of:

  • checklist answers
  • website URL
  • audit exports
  • PageSpeed or Lighthouse notes
  • Search Console notes
  • accessibility test notes
  • structured data test notes
  • discovery notes
  • uploaded files
  • spreadsheet rows
  • client meeting notes

If evidence is missing, ask follow-up questions before scoring. Do not invent evidence.

Workflow

  1. Confirm client/project context.
  2. Identify available evidence.
  3. Ask only the missing high-value questions.
  4. Score each readiness area from 0 to 10.
  5. Flag red flags even if the overall score is high.
  6. Produce both client-facing and internal LightSpeed sections.
  7. Recommend LightSpeed service/package routes.
  8. Output Markdown that can be pasted into a Google Doc.

Scoring areas

Score each from 0 to 10:

  1. Website foundations
  2. Content readiness
  3. Search, structured data and AI discoverability
  4. Brand, UX and design system readiness
  5. Data, privacy and governance
  6. Chatbot readiness

Calculate:

text
percentage = total score / 60 * 100

Round the percentage to a whole number before classifying it, then use these bands. The bands are contiguous, so every score falls in exactly one:

  • 0-30%: Not ready - foundation work required
  • 31-60%: Partly ready - priority gaps to fix
  • 61-80%: Mostly ready - suitable for guided AI adoption
  • 81-100%: Strong foundation - ready for governance and implementation planning

Required outputs

Always include:

  • Executive summary
  • Score table
  • Red flags
  • Missing evidence
  • Quick wins
  • Foundation work
  • Governance work
  • Implementation work
  • Tool recommendations
  • LightSpeed service/package recommendation
  • Client-facing next step
  • Internal LightSpeed notes

Consult references

  • references/scoring-model.md
  • references/red-flags.md
  • references/report-template.md
  • references/tool-checks.md

Have questions? Ping us on GitHub! 🐙 Made with 💚 by LightSpeedWP

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