screencast to sop

    by Elyas Shukri Elmi

    1

    Turn instructional videos into structured, schema-validated specs without hallucinating missing details.

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    Works with the AI tools you already use

    CClaude CodeCCursorCCodex CLIGGitHub CopilotGGemini CLIVVS CodeWWindsurf+15 more

    See it in action

    You say

    Extract the trading rules from this transcript. Do not guess the parameters if he doesn't say them. Focus on the entry and exit conditions.

    Your agent does

    { "direction": "LONG", "entry_conditions": [{ "indicator": "EMA", "indicator_param": "200", "condition": "price above", "comparison_value": null }], "exit_conditions": [], "confidence": 0.65, "notes": "Exit strategy not mentioned; risk per trade omitted." }

    What you get

    Convert trading videos into backtestable entry and exit rule sets.Generate structured SOPs from recorded expert walkthroughs.Extract compliance checklists from instructional training clips.Audit spoken procedures for technical gaps and vague instructions.

    About this skill

    The problem

    Instructional videos are often a "wall of prose" where experts mix precise rules with vague advice. Turning these recordings into actionable specs usually results in "smoothing," where an AI or human fabricates missing details just to make the document feel complete.

    What it does

    • Extracts structured procedures from spoken video content using a transcribe, extract, and validate pipeline.
    • Enforces strict "Iron Rules" to prevent the hallucination of parameters, rules, or steps not explicitly stated by the speaker.
    • Outputs schema-validated JSON with nullable fields to represent unstated information accurately.
    • Calculates confidence scores based on technical specificity rather than the speaker's fluency or confidence.
    • Distinguishes between low-confidence extractions and "no content" status for noise or motivational recordings.

    Frameworks & tools

    Faster-whisper for local transcription, Deepgram for hosted audio processing, and Pydantic for schema validation. Compatible with Groq and Hermes-class models for low-latency extraction.

    Why this beats prompting it yourself

    Generic prompts tend to "helpfully" fill in the blanks, like inventing a stop-loss percentage if a trader skips it. This skill is hard-coded to prioritize technical accuracy over prose fluency, ensuring you know exactly where a spec is incomplete.

    Use cases

    • Convert trading strategy walkthroughs into backtestable rule sets.
    • Transform recorded software onboarding sessions into structured SOPs.
    • Turn training videos into machine-readable compliance checklists.
    • Extract precise parameters from expert interviews for system modeling.

    Known limitations

    Not suitable for screen recordings where the primary information is visual (use screencast-to-sop instead). Free tiers for transcription and extraction are subject to provider rate limits.

    How to install

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

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