Built at the Autonomous Agents Hackathon · AWS Builder Loft, San Francisco · Feb 27, 2026
Autonomous multi-agent GitHub repository analyzer. Paste a repo URL, watch 6 AI agents clone it, walk every file, build a live Neo4j knowledge graph, surface vulnerabilities and code quality issues, and produce a prioritized fix plan — all in under a minute.
Event: Autonomous Agents Hackathon — Creators Corner
Date: Friday, February 27, 2026 · 9:30 AM – 7:30 PM
Venue: AWS Builder Loft · 525 Market St, San Francisco, CA
Prize Pool: $47k+
Sponsors powering this project:
| Sponsor | Role in Autonomix |
|---|---|
| Neo4j | Knowledge graph — every file, function, CVE, and relationship lives here |
| Fastino Labs | Primary fast classification & entity extraction via GLiNER-2 REST API |
| Yutori | Primary deep web research & vulnerability intelligence |
| OpenAI | Active fallback for Fastino/Yutori + deep code reasoning via GPT-4o |
| Tavily | Fast CVE search & NVD/GitHub Advisory lookups |
| AWS | Builder Loft hosting + infrastructure inspiration |
| Render | Deployment target |
- Paste any public GitHub URL → agents clone the repo instantly
- Mapper agent walks every file, builds a live Neo4j graph (nodes stream to UI in real-time)
- Quality agent analyzes code smells, dead code, complexity — Fastino fast scan → OpenAI deep pass
- Security agent runs Tavily CVE search + Yutori vulnerability research
- Pattern agent detects architectural anti-patterns and best practice violations
- Doctor agent generates a prioritized fix plan with before/after code examples
- Health score computed: letter grade + breakdown across 5 dimensions
The whole pipeline is live-streamed over WebSocket — you watch nodes appear in the graph and findings trickle in as the agents work.
| Service | Tech | Port |
|---|---|---|
| Frontend | Next.js 16 · TypeScript · Zustand | 3000 |
| Backend | FastAPI · SQLAlchemy · Alembic · Asyncio | 8000 |
| Database | PostgreSQL 16 | 5432 |
| Graph DB | Neo4j 5 Community (Docker) | 7474/7687 |
# 1. Clone and configure
cp .env.example .env
# Fill in your API keys (OpenAI alone is enough for a full run)
# 2. Boot everything
docker compose up --build -d
# 3. Open the app
open http://localhost:3000
# 4. Verify all integrations
curl http://localhost:8000/api/v1/health/integrations| URL | Description |
|---|---|
http://localhost:3000 |
Frontend app |
http://localhost:8000/docs |
Backend Swagger UI |
http://localhost:8000/api/v1/health |
Health check |
http://localhost:8000/api/v1/health/integrations |
Integration status (pre-demo test) |
http://localhost:7474 |
Neo4j Browser UI |
| Integration | Purpose | Status |
|---|---|---|
| Neo4j | Knowledge graph (local Docker — no external key) | ✅ Active |
| Fastino | Primary: fast classification & entity extraction | ✅ Wired — key activates full speed |
| Yutori | Primary: deep web research & reasoning | ✅ Wired — key activates research agents |
| OpenAI | Active fallback + deep reasoning (GPT-4o) | ✅ Active |
| Tavily | CVE search & web intelligence | ✅ Active |
| PostgreSQL | Primary relational store | ✅ Active |
| GitHub API | Repo metadata & rate limit boost | ⚙️ Optional |
Fallback architecture: Fastino and Yutori are the intended primaries. When their keys aren't set, OpenAI handles those tasks automatically — the system runs completely with only an OpenAI key. Activate Fastino/Yutori keys to get 99x faster classification and live web research.
# Required — OpenAI alone gives you a full working system
OPENAI_API_KEY=sk-proj-... # platform.openai.com
# Sponsor primaries — activate for full speed + features
FASTINO_API_KEY=pio_sk_... # fastino.ai — 99x faster classification
YUTORI_API_KEY=yt_... # platform.yutori.com — deep web research
TAVILY_API_KEY=tvly-... # app.tavily.com — CVE search
# Optional
GITHUB_TOKEN=ghp_... # higher rate limits + private repos
# Neo4j — runs in Docker, no cloud account needed
NEO4J_URI=bolt://neo4j:7687
NEO4J_USER=neo4j
NEO4J_PASSWORD=vibecheck_neo4j
# Auto-configured for Docker (do not change)
POSTGRES_USER=vibecheck
POSTGRES_PASSWORD=vibecheck_secret
POSTGRES_DB=vibecheckNeo4j runs inside Docker Compose — no separate install required.
URI (inside Docker): bolt://neo4j:7687
URI (from host): bolt://localhost:7687
Browser UI: http://localhost:7474
Username: neo4j
Password: vibecheck_neo4j
On first boot the backend auto-initializes: indexes, constraints, and schema. Browse your graph at http://localhost:7474:
-- All node types
MATCH (n) RETURN labels(n), count(n) ORDER BY count(n) DESC LIMIT 20
-- File graph for a specific analysis
MATCH (f:File {analysisId: "your-id"}) RETURN f LIMIT 50├── docker-compose.yml
├── .env / .env.example
├── frontend/ # Next.js 16 App Router
│ └── src/
│ ├── app/ # Pages (/, /analysis/[id])
│ ├── components/
│ │ ├── graph/ # GraphPanel, GraphCanvas (Cytoscape.js)
│ │ ├── findings/ # FindingsPanel, FindingDetail
│ │ ├── score/ # HealthScoreHero, ScoreBreakdown
│ │ ├── progress/ # AnalysisProgress, ActivityFeed (live agent feed)
│ │ └── layout/ # AppShell, SponsorFooter, TopBar
│ ├── stores/ # Zustand (analysisStore)
│ └── hooks/ # useAnalysisWebSocket
├── backend/
│ └── app/
│ ├── routers/ # analysis, findings, fixes, graph, health
│ ├── services/
│ │ ├── pipeline.py # 6-agent analysis pipeline
│ │ └── neo4j.py # Graph writes, schema init, blast radius
│ ├── clients/
│ │ ├── fastino.py # Fastino GLiNER-2 (primary)
│ │ ├── yutori.py # Yutori research (primary)
│ │ ├── openai_client.py # OpenAI fallback + deep reasoning
│ │ ├── tavily_client.py # CVE search
│ │ └── neo4j_client.py # Graph writer
│ └── agents/
│ └── orchestrator.py # High-level analysis orchestrator
├── docks/ # PRD, API reference, contracts, design
└── README.md
GET /api/v1/health Health check
GET /api/v1/health/integrations All sponsor integration status
POST /api/v1/analysis Start analysis { "repo_url": "https://..." }
GET /api/v1/analysis/{id} Status + results
GET /api/v1/analysis/{id}/graph Graph nodes + edges
GET /api/v1/findings/{id} Findings list
GET /api/v1/fixes/{id} Fix plan
WS /ws/{id} Real-time WebSocket stream
Full docs at http://localhost:8000/docs when running.
# Frontend
cd frontend && npm install && npm run dev
# Backend (needs postgres + neo4j via docker)
cd backend && pip install -r requirements.txt
uvicorn app.main:app --reload --port 8000
# DB migrations only
cd backend && alembic upgrade head
# Just spin up dependencies
docker compose up postgres neo4j -dBuilt with ❤️ at Creators Corner · Autonomous Agents Hackathon · San Francisco 2026