How do I install the 9router Chat skill?

Run npx skillmds@latest add decolua/9router-chat in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is 9router Chat safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with 9router Chat?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is 9router Chat free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published 9router Chat?

decolua (@decolua) published this skill. Their other Agent Skills are listed on their SkillMD profile.

9router Chat by decolua — Agent Skill

Name: 9router Chat
Rating: 4.5 (4 reviews)
Author: decolua

9router Chat

Chat / code generation via 9Router using OpenAI /v1/chat/completions or Anthropic /v1/messages format with streaming + auto-fallback combos. Use when the user wants to ask an LLM, generate code, summarize text, or run prompts through 9Router.

decolua Updated Sep 9, 2026

File contents

9Router — Chat

Requires NINEROUTER_URL (and NINEROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/decolua/9router/refs/heads/master/skills/9router/SKILL.md for setup.

Endpoints

POST $NINEROUTER_URL/v1/chat/completions — OpenAI format
POST $NINEROUTER_URL/v1/messages — Anthropic format

Discover

curl $NINEROUTER_URL/v1/models | jq '.data[].id'
# Per-model metadata (contextWindow, params)
curl "$NINEROUTER_URL/v1/models/info?id=openai/gpt-4o"

Combos (e.g. vip, mycodex) auto-fallback through multiple providers.

OpenAI format

curl -X POST $NINEROUTER_URL/v1/chat/completions \
  -H "Authorization: Bearer $NINEROUTER_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"openai/gpt-5","messages":[{"role":"user","content":"Hi"}],"stream":false}'

JS (OpenAI SDK):

import OpenAI from "openai";
const client = new OpenAI({ baseURL: `${process.env.NINEROUTER_URL}/v1`, apiKey: process.env.NINEROUTER_KEY });
const res = await client.chat.completions.create({
  model: "openai/gpt-5",
  messages: [{ role: "user", content: "Hi" }],
  stream: true,
});
for await (const chunk of res) process.stdout.write(chunk.choices[0]?.delta?.content || "");

Anthropic format

curl -X POST $NINEROUTER_URL/v1/messages \
  -H "Authorization: Bearer $NINEROUTER_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "Content-Type: application/json" \
  -d '{"model":"cc/claude-opus-4-7","max_tokens":1024,"messages":[{"role":"user","content":"Hi"}]}'

Response shape

OpenAI (/v1/chat/completions):

{ "id": "chatcmpl-...", "object": "chat.completion", "model": "openai/gpt-5",
  "choices": [{ "index": 0, "message": { "role": "assistant", "content": "Hello!" }, "finish_reason": "stop" }],
  "usage": { "prompt_tokens": 8, "completion_tokens": 2, "total_tokens": 10 } }

Streaming (stream:true) emits SSE: data: {choices:[{delta:{content:"..."}}]}\n\n ... data: [DONE]\n\n.

Anthropic (/v1/messages):

{ "id": "msg_...", "type": "message", "role": "assistant", "model": "cc/claude-opus-4-7",
  "content": [{ "type": "text", "text": "Hello!" }],
  "stop_reason": "end_turn", "usage": { "input_tokens": 8, "output_tokens": 2 } }

---name: 9router-chatdescription: Chat / code generation via 9Router using OpenAI /v1/chat/completions or Anthropic /v1/messages format with streaming + auto-fallback combos. Use when the user wants to ask an LLM, generate code, summarize text, or run prompts through 9Router.--- # 9Router — Chat Requires `NINEROUTER_URL` (and `NINEROUTER_KEY` if auth enabled). See https://raw.githubusercontent.com/decolua/9router/refs/heads/master/skills/9router/SKILL.md for setup. ## Endpoints - `POST $NINEROUTER_URL/v1/chat/completions` — OpenAI format - `POST $NINEROUTER_URL/v1/messages` — Anthropic format ## Discover ```bash curl $NINEROUTER_URL/v1/models | jq '.data[].id' # Per-model metadata (contextWindow, params) curl "$NINEROUTER_URL/v1/models/info?id=openai/gpt-4o" ``` Combos (e.g. `vip`, `mycodex`) auto-fallback through multiple providers. ## OpenAI format ```bash curl -X POST $NINEROUTER_URL/v1/chat/completions \ -H "Authorization: Bearer $NINEROUTER_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"openai/gpt-5","messages":[{"role":"user","content":"Hi"}],"stream":false}' ``` JS (OpenAI SDK): ```js import OpenAI from "openai"; const client = new OpenAI({ baseURL: `${process.env.NINEROUTER_URL}/v1`, apiKey: process.env.NINEROUTER_KEY }); const res = await client.chat.completions.create({ model: "openai/gpt-5", messages: [{ role: "user", content: "Hi" }], stream: true, }); for await (const chunk of res) process.stdout.write(chunk.choices[0]?.delta?.content || ""); ``` ## Anthropic format ```bash curl -X POST $NINEROUTER_URL/v1/messages \ -H "Authorization: Bearer $NINEROUTER_KEY" \ -H "anthropic-version: 2023-06-01" \ -H "Content-Type: application/json" \ -d '{"model":"cc/claude-opus-4-7","max_tokens":1024,"messages":[{"role":"user","content":"Hi"}]}' ``` ## Response shape OpenAI (`/v1/chat/completions`): ```json { "id": "chatcmpl-...", "object": "chat.completion", "model": "openai/gpt-5", "choices": [{ "index": 0, "message": { "role": "assistant", "content": "Hello!" }, "finish_reason": "stop" }], "usage": { "prompt_tokens": 8, "completion_tokens": 2, "total_tokens": 10 } } ``` Streaming (`stream:true`) emits SSE: `data: {choices:[{delta:{content:"..."}}]}\n\n` ... `data: [DONE]\n\n`. Anthropic (`/v1/messages`): ```json { "id": "msg_...", "type": "message", "role": "assistant", "model": "cc/claude-opus-4-7", "content": [{ "type": "text", "text": "Hello!" }], "stop_reason": "end_turn", "usage": { "input_tokens": 8, "output_tokens": 2 } } ```

Frequently asked questions