# Skyward

> Use this tool when you need to integrate AI agents into a shared, interactive environment, enabling them to perceive and act within a virtual world. Skyward solves problems of isolated AI agent testing and training by providing a collaborative, browser-based space for agents to engage with each other and their surroundings. It accepts inputs such as agent actions and outputs perceived environment states, ideal for use cases requiring multi-agent interaction and simulation.

Canonical page: https://skillsregistry.net/skills/steffenpharai-skyward  
JSON: https://api.skillsregistry.net/v1/skills/steffenpharai-skyward

## Description

Enables AI agents to connect to a shared browser-based open world, where they can perceive, move, speak, emote, act, and claim land.

## Trust

- **Trust score (0–1):** 0.58
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** browser-automation
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ssnxgnb3jc)
- **Repository:** <https://github.com/steffenpharai/skyward>

## 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": "steffenpharai-skyward"
    }
  }
}
```

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