# OpenClaw

This integration assumes you already have a valid chat running on OpenClaw with any supported provider.

***

#### Installation via ClawHub Skill

1. Install the latest version of the `fastrouter-setup` skill from ClawHub:

   ```
   openclaw skills install fastrouter-setup
   ```
2. Verify that the `fastrouter-setup` skill is present in your OpenClaw skills folder.
3. Restart your OpenClaw gateway.
4. In your chat, run:

   ```
   set up fastrouter with the api key sk-v1-xxxxxx
   ```

***

#### Reference

You can find the `skill.md` file:

* Attached below, or
* At: <https://fastrouter.ai/skills/openclaw/skill.md>

````xml
---
name: fastrouter-setup
description: "Add the FastRouter AI provider to OpenClaw with all available text and vision models, fetched live from the FastRouter API. Use when: (1) a user wants to set up FastRouter as a model provider, (2) a user says 'set up fastrouter', 'add fastrouter provider', or 'configure fastrouter' along with an API key, (3) a user wants to refresh/update their FastRouter model list. Triggers on phrases like 'set up fastrouter with API key sk-v1-xxxxx', 'add fastrouter provider', 'configure fastrouter', or 'update fastrouter models'."
---

# FastRouter Setup

Add the FastRouter AI provider to OpenClaw with all available text and vision models using only built-in tools (no script execution required).

## Inputs

- **API Key** (required): Starts with `sk-v1-` followed by a hex string. If not provided, ask for it.
- **Base URL** (optional): Defaults to `https://api.fastrouter.ai`

## Steps

### 1. Extract the API key

Parse the API key from the user's message. It starts with `sk-v1-`.

If no API key is found, ask the user for it. Do NOT proceed without one.

### 2. Fetch models

Use `web_fetch` to get the model list:

```
web_fetch url="https://api.fastrouter.ai/v1/models" extractMode="text"
```

### 3. Filter models

From the response JSON, keep only models where:
- `is_active` is true
- `architecture.output_modalities` includes "text"
- `architecture.input_modalities` includes "text" or "image"

For each qualifying model, extract:
- `id` — the model identifier
- `context_length` — context window size
- `top_provider.max_completion_tokens` — max output tokens (if 0 or missing, use min(context_length, 8192))
- Input types: list of "text" and/or "image" from input_modalities

### 4. Build provider config

Construct the provider object (do NOT include a "name" key — OpenClaw rejects it):

```json
{
  "baseUrl": "https://api.fastrouter.ai",
  "api": "openai-completions",
  "apiKey": "THE_API_KEY",
  "models": [
    {
      "id": "model/id",
      "name": "Display Name",
      "contextWindow": 128000,
      "maxTokens": 8192,
      "input": ["text", "image"],
      "cost": {"input": 0, "output": 0, "cacheRead": 0, "cacheWrite": 0},
      "reasoning": false
    }
  ]
}
```

### 5. Update openclaw.json

Use `read` to load `~/.openclaw/openclaw.json`.

Merge the provider into `models.providers.fastrouter`, preserving all other config.

Also add model references to `agents.defaults.models` — for each model, add:
```
"fastrouter/MODEL_ID": {}
```

Use `write` to save the updated config.

### 6. Restart gateway

```bash
openclaw gateway restart
```

This is the only step requiring user approval.

### 7. Report to user

Tell the user:
- How many models were added
- They can switch models with `/model fastrouter/MODEL_ID`
- Suggest popular models (claude, gpt, gemini, deepseek variants)

## Error Handling

- **API unreachable**: Tell the user the FastRouter API may be down, try again later
- **No qualifying models**: Warn that no text/image models were found
- **Config file missing**: Create the full structure from scratch
- **Invalid API key format**: Ask the user to double-check their key

## Notes

- Provider key is `fastrouter`
- Existing fastrouter config will be replaced with fresh model list
- All other providers and settings are preserved
- Cost is set to zero (FastRouter handles billing separately)
- Video-only and audio-only models are excluded

````


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.fastrouter.ai/integrations/openclaw.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.