Manage OpenClaw's use of models available at wisgate.ai API

Integrations

Query Wisgate for model pricing, capabilities, and configuration details. Use when adding a model to OpenClaw, comparing Wisgate pricing, or checking if a model supports a specific API type (Anthropic/OpenAI/Google). Also use when a less capable model needs help with Wisgate tasks.

Install

openclaw skills install @flofrie/wisgate-models

Wisgate Model Management

Canonical Model Catalog

Always check MODELS.json first before using Firecrawl or the API:

python3 -c "
import json
with open('MODELS.json') as f:
    data = json.load(f)
# List all models
for k, v in data.items():
    print(k)
"

To look up a specific model:

python3 -c "
import json, pprint
with open('MODELS.json') as f:
    data = json.load(f)
pprint.pprint(data.get('MODEL_ID'))
"

MODELS.json contains what you need for setting up the model in openclaw.json: openclaw_provider_key, api_type, context_window, max_output_tokens, notes (your and Florian's notes on that model), and all pricing fields.

Adding a Model to OpenClaw

Step 1: Look up the model in MODELS.json to get all fields.

Step 2: Add to agents.defaults.models in openclaw.json:

"PROVIDER_KEY/MODEL_ID": {}

e.g. "custom-api-wisgate-ai-openai/qwen3-max": {}

Step 3: Add the full model definition to the provider's models array:

{
  "id": "MODEL_ID",
  "name": "Display Name (Wisgate)",
  "contextWindow": 200000,
  "maxTokens": 33000,
  "input": ["text"],
  "cost": {
    "input": 0.50,
    "output": 2.00,
    "cacheRead": 0.10,
    "cacheWrite": 0.50
  },
  "reasoning": false
}

reasoning: true only for models with -thinking in the name
input: ["text"] for LLMs; ["text", "image"] for multimodal

When MODELS.json Is Missing a Model

Use Firecrawl to fetch from Wisgate:

FIRECRAWL_API_KEY=[see_below_for_where_to_find_the_key] \
python3 ~/.openclaw/workspace/skills/firecrawl-search/scripts/scrape.py \
"https://wisgate.ai/models/MODEL_ID"

Extract from output:

CTX → contextWindow
Input: **$X.XX** per 1M tokens → cost.input
Output: **$Y.YY** per 1M tokens → cost.output
Cache Read: / Cache Write: → cost.cacheRead / cost.cacheWrite

Then also add the new model to MODELS.json so future lookups work.

API Type Mapping

Endpoint Type	OpenClaw Provider	Base URL
Anthropic (Claude)	`custom-api-wisgate-ai`	`https://api.wisgate.ai/`
OpenAI compatible	`custom-api-wisgate-ai-openai`	`https://api.wisgate.ai/v1`
Google (Gemini)	`custom-api-wisgate-google`	`https://api.wisgate.ai/v1beta`

Firecrawl API Key

Stored in TOOLS.md