Organizational behavior, practiced on AI agents.
vstack is a curated library of 34 diagnostic patterns for AI agents and multi-agent systems, anchored in named organizational-behavior literature — Wharton's After-Action Review, Lencioni's Five Dysfunctions, Edmondson's Psychological Safety, Frei & Morriss's Trust Triangle, Schein's culture iceberg, Galbraith-Mintzberg structural fit — translated into runnable Python with public benchmarks and Substack-ready essays.
Most agent-observability tools capture what happened (traces). Most incident-response tools handle single events (a postmortem per alert). vstack ships a curated library of organizational practices — the same frameworks human teams use to learn, debate, escalate, and improve — implemented as patterns AI agents can run themselves.
Where the existing agent ecosystem treats failures as bugs to debug, vstack treats them as learning events to organize around.
- Python imports —
from vstack.lewin import LewinAttributionDetector - 34 per-pattern CLIs —
vstack-lewin analyze --trace trace.json - MCP server —
vstack-mcp servefor Claude Desktop, Cursor, Cline, Continue, Zed, etc. - REST API —
vstack-api serve(FastAPI on 127.0.0.1:8000) with auth, rate limiting, and observability baked in - Docker —
docker run ghcr.io/valani9/vstack:0.7.0 - Claude Code skills — 7 task-shaped
SKILL.mdfiles:/vstack-aar,/vstack-audit-crew,/vstack-post-incident, and more - Framework adapters — LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, Pydantic AI
- OpenAI Assistants + Anthropic Messages tool JSON — pure JSON, no install on the consumer side
- Open WebUI plugin — drop-in tool manifest pointing at a running
vstack-api - Tier B platform generators — Aider, Goose, Kiro, OpenClaw, Codex CLI, OpenCode (
vstack-config gen-platform) - Browser dev tooling —
vstack-browserscrapes agent traces from LangSmith / Phoenix / Helicone / Langfuse / Arize - First-run smoke (
vstack-hello) — 30-second end-to-end demo with graceful no-key fallback
- Quick start — install + first detection in 60 seconds.
- The 5-layer pattern shape — how every pattern is documented + implemented + demoed + benchmarked + written up.
- Composition runbook — how the 34 patterns chain into real diagnostic workflows.
pip install valanistack # core library + 34 CLIs
pip install 'valanistack[anthropic]' # + Anthropic client
pip install 'valanistack[mcp]' # + MCP server
pip install 'valanistack[api]' # + FastAPI REST surface
pip install 'valanistack[adapters]' # + LangChain/LangGraph/CrewAI/LlamaIndex/Pydantic AI
pip install 'valanistack[all]' # everythingPython 3.11+ required. MIT-licensed. Sole author: Ilhan Valani (valani@bu.edu).