dbreunig

dbreunig / scaffold-docs-skill

Public

A skill for writing technical documentation for human readers, iteratively, with author reviews at each step.

40
2
89% credibility
Found Jun 01, 2026 at 40 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
AI Summary

Scaffold Docs is a skill that helps AI assistants write better technical documentation for code libraries. It guides the creation of three-tier documentation: a narrative Getting Started tutorial, topic-focused Diving Deeper guides, and a lookup-oriented Reference section. The process builds documentation in passes—structure first, then headers, then full prose—with human review checkpoints at each stage. Key principles include writing for a specific audience, building the reader's mental model before listing API details, explaining why over what, and maintaining prose quality standards. The author remains in the loop throughout, providing guidance on structure, empathy, and writing quality, especially for the Getting Started section.

How It Works

1
💡 Discover the Documentation Problem

You realize that AI-generated documentation often lacks the structure and warmth that human readers need to truly understand a library.

2
📋 Find the Scaffold Docs Skill

You discover a tool designed to help AI assistants write better documentation by following proven principles: writing for your audience, building mental models, and scaffolding information.

3
⚙️ Install the Skill

You copy or link the skill folder into your Claude Code assistant's skills directory so it's ready to use whenever you need it.

4
🚀 Start the Documentation Process

You invoke the skill with a simple command, and your assistant begins building documentation in three tiers: a getting started tutorial, deeper topic guides, and a reference section.

5
Review and Refine Together
✅
Approve and Continue

You approve the current section and the process moves forward to the next pass

✏️
Request Changes

You ask for adjustments and your assistant revises before proceeding

6
📖 Receive Complete Documentation

After iterative passes and your guidance, you receive polished documentation: a narrative tutorial, topic files organized by intent, and a clean reference guide.

🎉 Your Library Has Clear Documentation

Readers can now understand your library quickly, build a mental model of how it works, and find the details they need—all thanks to documentation written with human care.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 40 to 40 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is scaffold-docs-skill?

This is a skill for AI coding assistants that generates technical documentation through a structured, iterative process with built-in human checkpoints. Rather than producing docs in one shot, it breaks the work into passes: first structure, then headers, then full prose. The agent pauses between each pass for your review and won't continue until you approve. It produces a three-tier documentation set: a narrative Getting Started tutorial, topic-based Diving Deeper sections organized around intent, and per-module Reference material. The skill embeds principles like writing for a specific audience, building mental models before listing API surface, and explaining why over what.

Why is it gaining traction?

Documentation is where AI assistants consistently fall short. They generate technically accurate but structurally confused prose that fails readers. This skill addresses that by forcing the agent to think about audience and structure before writing. The human review gates prevent wasted effort on prose that misses the point. The three-tier structure gives you a clear mental model for what good library documentation should look like. Developers are drawn to the explicit focus on quality writing standards and the acknowledgment that agents need human guidance on empathy and structure.

Who should use this?

Library maintainers who want solid documentation but dread writing it themselves. Technical leads evaluating AI tooling for their workflow. Teams that have tried AI-generated docs and been disappointed by the results. If you maintain an open source library or internal package and keep putting off the docs, this gives you a structured process to work through with an AI assistant doing the drafting. It's less useful if you need reference documentation without the tutorial layer.

Verdict

The concept is solid and the principles are sound, but this is a small, early-stage project with 40 stars and a credibility score under 1%. The README is well-written but there's no visible test coverage or release history. Worth exploring if you're building library documentation and want a structured process, but don't bet a production workflow on it yet. Watch the repo for maturity.

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.