relay-to-agent
Relay messages to AI agents on any OpenAI-compatible API. Supports multi-turn conversations with session management. List agents, send messages, reset sessions.
Best use case
relay-to-agent is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Relay messages to AI agents on any OpenAI-compatible API. Supports multi-turn conversations with session management. List agents, send messages, reset sessions.
Teams using relay-to-agent should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/relay-to-agent/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How relay-to-agent Compares
| Feature / Agent | relay-to-agent | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Relay messages to AI agents on any OpenAI-compatible API. Supports multi-turn conversations with session management. List agents, send messages, reset sessions.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Relay To Agent
Send messages to AI agents on any OpenAI-compatible endpoint. Works with Connect Chat, OpenRouter, LiteLLM, vLLM, Ollama, and any service implementing the Chat Completions API.
## List available agents
```bash
node {baseDir}/scripts/relay.mjs --list
```
## Send a message to an agent
```bash
node {baseDir}/scripts/relay.mjs --agent linkedin-alchemist "Transform this article into a LinkedIn post"
```
## Multi-turn conversation
```bash
# First message
node {baseDir}/scripts/relay.mjs --agent connect-flow-ai "Analyze our latest campaign"
# Follow-up (same session, agent remembers context)
node {baseDir}/scripts/relay.mjs --agent connect-flow-ai "Compare with last month"
```
## Reset session
```bash
node {baseDir}/scripts/relay.mjs --agent linkedin-alchemist --reset "Start fresh with this article..."
```
## Options
| Flag | Description | Default |
|------|-------------|---------|
| `--agent ID` | Target agent identifier | (required) |
| `--reset` | Reset conversation before sending | off |
| `--list` | List available agents | — |
| `--session ID` | Custom session identifier | `default` |
| `--json` | Raw JSON output | off |
## Configuration
### agents.json
Configure agents and endpoint in `{baseDir}/agents.json`:
```json
{
"baseUrl": "https://api.example.com/v1",
"agents": [
{
"id": "my-agent",
"name": "My Agent",
"description": "What this agent does",
"model": "model-id-on-the-api"
}
]
}
```
### Environment variables
```bash
export RELAY_API_KEY="sk-..." # API key (required)
export RELAY_BASE_URL="https://..." # Override base URL from config
export RELAY_CONFIG="/path/to/agents.json" # Custom config path
```
## Compatible Services
- **Connect Chat** — `api.connectchat.ai/api`
- **OpenRouter** — `openrouter.ai/api/v1`
- **LiteLLM** — `localhost:4000/v1`
- **vLLM** — `localhost:8000/v1`
- **Ollama** — `localhost:11434/v1`
- **Any OpenAI-compatible API**
## Session Management
Sessions are stored locally at `~/.cache/relay-to-agent/sessions/`. Each agent+session combination keeps up to 50 messages. Use `--session` for parallel conversations with the same agent.Related Skills
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