llmcouncil-router

# LLM Council Router

Route any prompt to the best-performing LLM. The API finds the top model for a given query based on thousands of peer-reviewed council deliberations — then you call that model directly.

## Base URL

```
https://clawbot.llmcouncil.ai
```

## Authentication

Use the `X-API-Key` header with your LLM Council API key.

```
X-API-Key: clwb_YOUR_KEY_HERE
```

Get a free key at [llmcouncil.ai/developers](https://llmcouncil.ai/developers).

## Endpoint: POST /v1/route

Find the best-performing model for a query.

### Request

```json
{
  "query": "Explain quantum entanglement simply",
  "k": 20
}
```

| Field | Type | Required | Description |
|-------|------|----------|-------------|
| `query` | string | Yes | The prompt or question to route |
| `k` | integer | No | Number of past evaluations to consider (default: 20) |

### Response

```json
{
  "query": "Explain quantum entanglement simply",
  "nearest_councils": 20,
  "model": "anthropic/claude-sonnet-4",
  "relevance": 0.8234,
  "confidence": 0.65,
  "model_rankings": [
    { "rank": 1, "model": "anthropic/claude-sonnet-4", "nearby_wins": 13, "nearby_appearances": 20 },
    { "rank": 2, "model": "openai/gpt-4.1", "nearby_wins": 5, "nearby_appearances": 18 }
  ]
}
```

| Field | Type | Description |
|-------|------|-------------|
| `model` | string | Top recommended model ID (matches OpenRouter catalogue) |
| `relevance` | float (0–1) | How closely matched evaluations relate to your query. Above 0.75 is strong. |
| `confidence` | float (0–1) | How decisively the top model outperforms alternatives. Higher = clearer winner. |
| `nearest_councils` | integer | Number of relevant past evaluations used |
| `model_rankings` | array | All models ranked by performance across matched evaluations |

## How to use this skill

When the user asks you to find the best model for a task, or when you need to decide which LLM to use:

1. **Call the routing API** with the user's query:

```bash
curl -X POST https://cla...