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open-scaffold

Record AI-assisted work sessions with transcripts, receipts, and test results.

14|1|Updated Apr 12, 2026
Search Tags:#code review#repository management#process tracking#work record#AI-assisted work
One-click install
npx skills add https://github.com/graphanov/open-scaffold --skill open-scaffold
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: open-scaffold
Source: https://github.com/graphanov/open-scaffold/tree/main
Command: npx skills add https://github.com/graphanov/open-scaffold --skill open-scaffold

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

Open Scaffold addresses the issue of lost context and memory in AI-assisted work, providing a structured and durable record of work sessions for future reference and review.

Core Features & Use Cases

  • Work Record Creation: Automatically records the work performed by AI agents, including transcripts, receipts, and test results.
  • Handoff Packets: Compiles work records into secure, redacted packets for handoff to different agents or sessions.
  • Review and Gate: Enables review and authorization of work attempts with clear feedback and retry mechanisms.
  • Use Case: For a team using AI for code review, Open Scaffold can ensure that each code change is reviewed and authorized before being merged, maintaining a detailed record of the process.

Quick Start

To start using Open Scaffold, run the following command in your project directory:

npx open-scaffold@latest first-run

Frequently Asked Questions about open-scaffold

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I maintain a work record for AI-assisted coding sessions?▼

To maintain a work record for AI-assisted coding, use a structured tracking process that logs missions, plans, run records, and review decisions. This ensures your AI-assisted work remains traceable and accountable for future reference.

What is the best way to track AI code review and process tracking in a repository?▼

The best way to track AI code review is to implement a review and gate mechanism that authorizes work attempts with clear feedback and retries. This maintains a detailed process tracking record for each code change before merging.

How do I compile AI work records into handoff packets for different agents?▼

You compile AI work records into handoff packets by securely redacting transcripts, receipts, and test results. This creates a durable context packet that can be safely handed off to different coding agents or sessions.

Can I use repository management tracking with any coding agent or runtime?▼

Yes, you can use repository management tracking with any coding agent or runtime. The process requires the Open Scaffold CLI to structure the work records, ensuring broad compatibility across different AI tools.

How do I set up Open Scaffold for repository management?▼

To set up Open Scaffold for repository management, run the command `npx open-scaffold@latest first-run` in your project directory. This initializes the structured work record tracking environment for your codebase.

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