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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
What started as an opinionated Claude Code setup kit is now an autonomous AI engineering command center
| Date | Stars |
|---|---|
| 2026-07-31 | 705 |
| 2026-08-01 | 705 |
| 2026-08-06 | 705 |
Today
— stars today
This week
— stars this week
This month
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Momentum
0.0
growth rate 0.00%/day
# Claude Bootstrap + Maggy
> **Turn Claude Code into a self-reviewing, test-enforced engineering system that remembers context across sessions — then route work across 13 models from a single dashboard.**
Claude Bootstrap is an installable config pack (skills, hooks, rules, templates) for Claude Code. Maggy is the optional local server that adds multi-model routing, a web dashboard, intent-driven protocols, and plugin orchestration. Both live in this repo. Start with Bootstrap; add Maggy when you need the harness.
[](maggy/tests/)
[](CHANGELOG.md)
[](https://github.com/alinaqi/maggy/stargazers)
[](LICENSE)
**1100+ tests. 67 skills. 15 MCP tools. Used daily across production codebases.**
---
## Who This Is For
- **Solo engineers** using Claude Code who want TDD enforcement, quality gates, and memory that survives context compaction — without changing their workflow
- **Teams** routing work across Claude, DeepSeek, Kimi, Gemini, and Codex from a single dashboard with cost-aware model selection
- **Platform engineers** building AI-assisted developer tooling who need a reference implementation with intent tracking, protocol execution, and plugin architecture
---
## Choose Your Path
| | Claude Bootstrap | Maggy Harness |
|---|---|---|
| **What it is** | Skills, hooks, rules installed into `~/.claude/` | Local FastAPI server + web dashboard |
| **Install time** | ~30 seconds | ~5 minutes (Python 3.11+, API keys) |
| **Requires** | Claude Code (also works with Codex, Kimi, Gemini CLI) | Everything in Bootstrap + Python + optional Docker |
| **You get** | TDD enforcement, 67 skills, quality gates, ADR reviews, iCPG, Mnemos memory | All of Bootstrap + 13-tier routing, skill protocols, Telos testing, Cortex MCP, plugins, dashboard |
### Bootstrap — 30-second install
```bash
git clone https://github.com/alinaqi/maggy.git
cd maggy && ./install.sh
```
Your next Claude Code session picks it up automatically.
### Full Harness — zero-config
```bash
pipx install maggy-harness # or: pip install maggy-harness
maggy bootstrap # installs skills, hooks, ~/bin model wrappers, plugins
maggy serve # auto-configures from your local repos,
# then opens the dashboard at localhost:8080
```
(or from source: `cd maggy && ./install.sh && maggy serve`)
No API keys required to start — Maggy runs in local mode and, on first launch,
discovers your local git repos and opens the dashboard pointed at them. Add
`GITHUB_TOKEN` / `ANTHROPIC_API_KEY` later only if you want GitHub sync or
API-model features. See [GETTING_STARTED.md](GETTING_STARTED.md) for details.
---
## What It Looks Like in Practice
**Routing a task:**
```
You: "review the auth middleware for timing attacks"
→ Blast score: 8/10 (security + architecture)
→ Routed to: Claude (Tier 11)
→ ADR gate: found docs/adr/0003-jwt-strategy.md → injected as context
→ Review runs with full architectural context
```
**Skill Protocol execution:**
```
You: "push to git"
→ Intent matched: git-push protocol
→ ✅ lint (2.1s)
→ ✅ typecheck (4.3s)
→ ✅ tests (11.2s)
→ ✅ stage
→ ✅ commit [AI-generated: "fix: resolve token refresh race condition"]
→ ✅ push
```
**Fatigue-aware memory:**
```
Session fatigue: 0.61 (PRE-SLEEP)
→ Mnemos: auto-checkpoint written
→ Micro-consolidation: 3 ResultNodes compressed
→ iCPG context injected: 2 ReasonNodes, 1 constraint
→ Context freed: ~18k tokens
```
---
## The Problem This Solves
You're using Claude Code. It's impressive — but:
- It picks the most expensive model for everything, including trivial tasks
- Context fills up, state is lost, you re-explain yourself every session
- There's no enforcement: code quality, test coverage, and AExcerpt of 13,270 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:c158ab9f3feea2d0, topic:ai-coding, topic:developer-tools