# covas

> covas — sevenking-dev-covas. Use this tool when you need to visually annotate images with shapes and marks to clarify or highlight specific details, solving problems like complex image analysis or communication. It takes an image as input and produces an annotated image as output, which can be sent back into conversations for further discussion. Ideal for use cases where visual explanation or emphasis is required, such as design review or defect identification.

Canonical page: https://skillsregistry.net/skills/sevenking-dev-covas  
JSON: https://api.skillsregistry.net/v1/skills/sevenking-dev-covas

## Description

Single-image annotation workspace — draw boxes, arrows, freehand marks, send annotated results back into Codex conversations.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/sevenking-dev/covas)

## 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": "sevenking-dev-covas"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sevenking-dev-covas` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sevenking-dev-covas/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