# ChannelTerm

> ChannelTerm — akira-init1-channelterm. Use this tool when you need to collaborate with humans and AI agents on terminal sessions, particularly for serial and hardware debugging tasks. ChannelTerm solves problems of remote collaboration and debugging by providing a shared terminal interface. It accepts input from users and AI agents, and outputs a unified view of the terminal session, making it ideal for use cases like git-based project debugging and hardware development.

Canonical page: https://skillsregistry.net/skills/akira-init1-channelterm  
JSON: https://api.skillsregistry.net/v1/skills/akira-init1-channelterm

## Description

Shared terminal sessions for humans and AI agents, starting with serial and hardware debugging.

## Trust

- **Trust score (0–1):** 0.58
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/akira-init1/ChannelTerm)

## 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": "akira-init1-channelterm"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/akira-init1-channelterm` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/akira-init1-channelterm/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