messy files to sop training system
by nowrich
Turns messy files and transcripts into synchronized, evidence-traced SOPs and training systems.
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Works with the AI tools you already use
See it in action
You say
I have a transcript of a training call and three screenshots of our new CRM. Build a full SOP and training pack, trace everything to the sources, and flag any gaps in the process.
Your agent does
I have registered 4 sources (S1-S4). SOP Core: Step 1: Open CRM Dashboard [S3-C1] Step 2: Input lead data [S1-C12] GAP: Manager approval workflow not defined in sources. Training Pack:
- One-Page Guide generated.
- Quiz: Q1. Where do you start? A: Dashboard [S3-C1]. Appendices included.
What you get
About this skill
The problem
Process documentation is often scattered across messy transcripts, screenshots, and old PDFs, leading to "knowledge rot" where instructions are invented or assumed. Developers and ops teams struggle to maintain a single source of truth that is 100% verifiable against raw evidence.
What it does
- Extracts atomic evidence from messy notes, meeting transcripts, tool screenshots, and legacy PDFs.
- Generates a synchronized SOP Core where every step, decision, and quality check includes a direct source trace ID.
- Produces a complete training pack including a one-page reference, onboarding lesson, and evidence-backed quiz.
- Logs procedural gaps and conflicting instructions explicitly instead of making assumptions or "hallucinating" fixes.
- Audits existing documentation to identify orphan instructions that lack source evidence.
Why this beats prompting it yourself
Generic prompts often smooth over contradictions or fill in missing steps with common sense, creating dangerous inaccuracies. This skill enforces a strict non-invention contract, ensuring that every piece of output is anchored to a specific source ID and registry entry.
Use cases
- Converting a recorded handoff call into a formal SOP and trainee quiz.
- Consolidating scattered Slack screenshots and markdown notes into a synchronized training system.
- Auditing legacy documentation to find steps that no longer align with current tool screenshots.
- Updating a production process by merging new evidence into an existing documentation set with a full change log.
Known limitations
Cannot resolve procedural conflicts automatically, these are flagged for user decision. Requires manual confirmation for blurry screenshots or unreadable OCR text.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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