Transform any repo to G-Stack quality. One install, fully automated.
Point this framework at any project and it will analyze, audit, create skills, apply templates, and verify -- bringing your repo up to the standard of Garry Tan's gstack (the most sophisticated AI engineering workflow in production).
Your Repo (before) Your Repo (after)
------------------ -----------------
README.md README.md (improved)
src/ src/
package.json --> package.json
ETHOS.md (builder philosophy)
CLAUDE.md (dev guide + commands)
ARCHITECTURE.md (technical decisions)
VERSION (4-digit semver)
CHANGELOG.md (user-facing notes)
TODOS.md (prioritized work)
skills/
plan/SKILL.md
build/SKILL.md
test/SKILL.md
ship/SKILL.md
... (custom to your project)
# 1. Clone into your Claude Code skills
git clone https://github.com/YOUR_USER/gstack-framework.git ~/.claude/skills/gstack-framework
cd ~/.claude/skills/gstack-framework && ./setup
# 2. Open any project in Claude Code and run:
/gstack-frameworkThat's it. The orchestrator walks you through everything:
- Analyze -- Scans your repo structure, tech stack, docs, tests, CI/CD
- Audit -- Scores it 0-100 against G-Stack quality standards
- Find Skills -- Identifies where skills are needed across your workflow
- Find Agents -- Identifies multi-agent and chaining opportunities
- Create Skills -- Generates high-quality SKILL.md files for each gap
- Apply Template -- Adds ETHOS.md, CLAUDE.md, ARCHITECTURE.md, etc.
- Verify -- Checks everything was applied correctly, produces final score
Run any step independently:
| Skill | What it does |
|---|---|
/gf-analyze |
Scan repo structure, tech stack, existing docs and skills |
/gf-audit |
Score repo 0-100 against G-Stack standards |
/gf-find-skills |
Identify where skills should exist across the dev lifecycle |
/gf-find-agents |
Find multi-agent and cross-skill chaining opportunities |
/gf-create-skills |
Generate SKILL.md files for approved skills |
/gf-apply |
Apply full G-Stack template (ETHOS, CLAUDE.md, ARCHITECTURE, etc.) |
/gf-verify |
Verify all components applied correctly, produce final score |
- ETHOS.md -- Your builder philosophy (completeness principle, search-before-building)
- CLAUDE.md -- Dev commands, project structure, conventions (from actual package.json/Makefile)
- ARCHITECTURE.md -- Technical decisions and WHY (from actual tech stack)
- VERSION -- 4-digit semver (MAJOR.MINOR.PATCH.MICRO)
- CHANGELOG.md -- User-facing release notes format
- TODOS.md -- Prioritized work items (P0-P4)
Each generated skill follows G-Stack patterns:
- YAML frontmatter with trigger phrases
- Phase-based workflow (Context -> Analysis -> Action -> Verification -> Report)
- Explicit stop conditions AND "never stop for" lists
- Voice directive (bans AI slop vocabulary)
- AskUserQuestion format (re-ground, simplify, recommend, options)
- Completion Status Protocol (DONE, BLOCKED, NEEDS_CONTEXT)
- Evidence-based verification ("confidence is not evidence")
gstack-framework/
|-- skills/ # The active tools (8 skills)
|-- templates/ # Raw templates with {{PLACEHOLDER}} syntax
|-- checklists/ # Scoring rubrics and quality criteria
|-- reference/ # Analysis docs + cloned gstack repo
| |-- GSTACK-DEEP-ANALYSIS.md
| |-- GSTACK-TEMPLATE-FRAMEWORK.md
| |-- patterns.md
| |-- anti-patterns.md
| |-- gstack/ # The original G-Stack repo (reference)
|-- setup # One-command installer
|-- CLAUDE.md # Dev guide for this framework
Every generated skill must pass the skill quality checklist:
- Proper YAML frontmatter (name, description with triggers, allowed-tools)
- Iron Law / Hard Gate (the one constraint that cannot be violated)
- Phase-based workflow with numbered phases
- Verification step requiring evidence
- Stop conditions (both "stop for" and "never stop for")
- Voice directive with banned vocabulary
- Completion Status Protocol with escalation rules
- No AI slop (delve, crucial, robust, comprehensive, nuanced...)
The framework never overwrites existing files without asking. For every file that already exists, it shows a diff and lets you approve or skip.
This framework extracts and templatizes the patterns from Garry Tan's gstack -- 28 production skills covering the entire AI engineering workflow. See reference/GSTACK-DEEP-ANALYSIS.md for the complete breakdown.
MIT