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    ai-opportunity-audit

    by Roy Yuen

    Turn discovery intake into professional, ranked AI automation roadmaps and executive audit reports.

    Updated Jun 2026
    73 views
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    $7

    · or 35 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Generate client-ready AI transformation roadmaps from discovery notes.
    • Score and rank automation opportunities based on effort and business impact.
    • Ready for Claude Code
    • Includes example output and usage patterns
    • Instant install

    Sample input

    Run an audit for Smith & Co Plumbing. They use HubSpot and Gmail but miss enquiries. Focus on lead intake and quote follow-ups to reduce admin time. Set risk to medium and save to report.md.

    Sample output

    Recommended: 'Lead Intake Automation' Score: 8.5/10 (Impact: High, Effort: Low) Evidence: Matches pain point 'missed enquiries' and tool 'HubSpot'. Roadmap:

    • 30 Days: Automated Gmail-to-HubSpot lead capture.
    • 60 Days: Quote follow-up sequencing.
    • 90 Days: KPI reporting dashboard via Google Sheets.

    About This Skill

    What it does

    This skill automates the creation of professional AI Opportunity Audits, transforming structured discovery data into agency-ready consulting deliverables. It takes business inputs—such as workflows, pain points, and existing tech stacks—and generates a ranked recommendation map, a staged 30/60/90-day roadmap, and detailed risk assessments.

    Why use this skill

    For agencies and consultants, manual discovery analysis is time-consuming and prone to inconsistency. This skill provides a deterministic, evidence-backed framework that ensures every recommendation is tied directly to client-provided data. It helps you move from "initial chat" to "professional proposal" in seconds, maintaining high standards for technical feasibility and business impact without the fluff of generic AI advice.

    Supported tools & outputs

    • Frameworks: Compatible with Python/PowerShell automation environments.
    • Formats: Produces both Markdown (for client presentation) and JSON (for CRM or internal tool ingestion).
    • Structure: Follows a strict output contract including executive summaries, prioritized opportunity scoring (impact/effort/readiness), and tooling notes.

    By using an evidence-based scoring logic tailored to real-world business workflows like CRM hygiene and lead intake, this skill ensures your advisory services are practical, grounded, and ready for implementation.

    Use Cases

    • Generate client-ready AI transformation roadmaps from discovery notes.
    • Score and rank automation opportunities based on effort and business impact.
    • Produce structured JSON data for AI implementation proposals.
    • Standardize the pre-sales discovery process for automation agencies.

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    Permissions

    Allowed Hosts

    example.com

    File Scopes

    client-intake-scope-builder/**

    Claude Code, OpenClaw, and CLI-based agents supporting Python/PowerShell execution.

    Creator

    Frequently Asked Questions

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