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    CJM Builder Pro

    by Ehab

    Turn raw research into offline HTML journey maps with emotion curves and a live English/Arabic toggle.

    Updated Jul 2026
    Security scanned
    Works fully offline: no API key

    $29

    · or 145 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Convert raw transcripts into visual AS-IS journey maps with evidence tagging.
    • Generate future-state TO-BE maps with target emotion curves.
    • file_write, file_read automation included
    • Ready for Works fully offline: no API key
    • Instant install

    Media gallery

    See it in action

    You say

    Run /cjm on the ./user-interviews folder to create an AS-IS map and report for our onboarding flow. Generate it in both English and Arabic.

    Your agent does

    Completed. I analyzed 12 interview transcripts. Found 4 critical pain points in the 'Account Setup' phase.

    • Generated: cjm-workspace.html
    • Features: 5-step journey, emotion curve, evidence-linked pain points, and RTL Arabic support. Open the file in any browser to view.

    About This Skill

    The problem

    Synthesizing hundreds of interview notes and survey results into a structured journey map takes days of manual tagging. Traditional design tools are often locked behind subscriptions, lack RTL support for global clients, and require uploading sensitive research data to the cloud.

    What it does

    • Generates a portable, offline HTML workspace containing AS-IS and TO-BE journey maps plus a research report.
    • Builds a column-aligned emotion curve that visually maps user sentiment across every journey phase.
    • Includes a live English and Arabic (RTL) toggle to flip the entire interface and content for bilingual presentations.
    • Traces every pain point back to specific evidence found in the source research files.
    • Exports data to Markdown, CSV, JSON, and print-ready PDF directly from the generated workspace.

    Why this beats prompting it yourself

    Standard LLM prompts struggle to maintain alignment between emotion curves and journey steps in a visual format. This skill uses a specialized engine to ensure data integrity across swimlanes while keeping the entire output in a single, local HTML file that requires zero hosting or API dependency.

    Use cases

    • Turn a folder of raw interview transcripts into a client-ready discovery report.
    • Brainstorm future-state service designs by generating TO-BE maps alongside current friction points.
    • Present research findings to Middle Eastern stakeholders using the native RTL Arabic toggle.
    • Audit research gaps by identifying where data is too thin to support a journey phase.

    Known limitations

    The tool requires structured text input (.md or .txt) and cannot ingest raw audio or video files without prior transcription.

    Use Cases

    • Convert raw transcripts into visual AS-IS journey maps with evidence tagging.
    • Generate future-state TO-BE maps with target emotion curves.
    • Create bilingual journey maps with full RTL Arabic support for presentations.
    • Export journey data to CSV or JSON for integration with other product tools.

    How to install

    Drop the file into your AI tool. Works with Claude, Cursor, ChatGPT, and 20+ more.

    Reviews

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    Only users who have downloaded or purchased this skill can leave a review.

    Security Scanned

    Passed automated security review

    Permissions

    Write Files
    Read Files

    File Scopes

    pro/**

    This skill reads the user's local research files and writes a self-contained HTML workspace (plus optional Markdown/CSV/JSON exports) to a local path. It makes no network calls, runs no shell/install scripts, and reads no environment variables. The auto-detector flagged Terminal/Shell and Network only because the bundled GUIDE shows copy/paste install commands and the docs state "no network calls"; the skill itself needs neither. Offline behavior is verifiable with a single grep (command in README).

    Tags

    ux-research
    journey-mapping
    arabic-rtl
    data-visualization
    product-design
    customer-journey-map
    cx
    service-design

    Works fully offline: no API key, no network calls, no telemetry. First-class on Claude Code; the /cjm command and knowledge skills are plain SKILL.md-standard Markdown, adaptable to any compatible agent. Reads .md / .txt / .docx research; the workspace opens in any modern browser.

    Creator

    E

    Frequently Asked Questions

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