# vstack

> vstack — valani9-vstack. Use this tool when you need to analyze and improve the organizational behavior of AI agents, solving problems related to team dynamics, communication, and performance. It applies 34 diagnostic patterns from renowned OB literature to 12 invocation surfaces, including Python, CLIs, and REST. This tool is ideal for use cases where AI agents require optimized collaboration and decision-making, with outputs informing strategic improvements and inputs from various technical interfaces.

Canonical page: https://skillsregistry.net/skills/valani9-vstack  
JSON: https://api.skillsregistry.net/v1/skills/valani9-vstack

## Description

AI agents fail like junior teammates, looping on bad ideas, ignoring feedback, and escalating commitment. vstack ports 34 of the most-cited organizational-behavior frameworks so you can diagnose your agents the same way you'd diagnose your team.

## Trust

- **Trust score (0–1):** 0.62
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/valani9/vstack)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "valani9-vstack"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/valani9-vstack` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/valani9-vstack/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt