# agent-opfor

> agent-opfor — keyvaluesoftwaresystems-agent-opfor. Use this tool when you need to simulate adversarial scenarios for AI agents and MCP servers, emulating opponent forces to test and improve their performance and decision-making. It provides open-source adversary emulation, allowing for realistic threat simulations and enhanced security testing. Ideal for use cases requiring robust AI training and evaluation, such as cybersecurity and tactical strategy development.

Canonical page: https://skillsregistry.net/skills/keyvaluesoftwaresystems-agent-opfor  
JSON: https://api.skillsregistry.net/v1/skills/keyvaluesoftwaresystems-agent-opfor

## Description

Open-source adversary emulation for AI agents and MCP servers.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-27

## Source

- **Source listing:** [GitHub](https://github.com/KeyValueSoftwareSystems/agent-opfor)

## 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": "keyvaluesoftwaresystems-agent-opfor"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/keyvaluesoftwaresystems-agent-opfor` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/keyvaluesoftwaresystems-agent-opfor/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