add-model
Add a new model to a live LiteLLM proxy. Walks the user through picking a provider, entering the deployment name and credentials, calls POST /model/new, then test-calls the model to confirm it routes correctly. Use when the user wants to add, register, deploy, or configure a new model on a LiteLLM proxy instance.
How do I install this agent skill?
npx skills add https://github.com/berriai/litellm-skills --skill add-modelIs this agent skill safe to install?
- Gen Agent Trust Hubpass
The skill is a management tool for LiteLLM proxies that allows adding and testing model configurations. It is authored by the vendor of the software it manages and references official documentation. The primary security consideration is an indirect prompt injection surface where user-provided inputs are interpolated into shell commands without explicit sanitization instructions.
- Socketpass
No alerts
- Snykfail
Risk: HIGH · 1 issue
What does this agent skill do?
Add Model
Add a new LLM to a live LiteLLM proxy.
Setup
Ask for these if not already known:
LITELLM_BASE_URL — e.g. https://my-proxy.example.com
LITELLM_API_KEY — proxy admin key
API reference: https://litellm.vercel.app/docs/proxy/model_management
Ask the user
- Public model name — what callers will send in
"model": "..."(e.g.gpt-4o,my-claude,llama3) - Provider — pick from the table below
- Credentials — whatever that provider needs
Provider table
| Provider | litellm_params.model | Extra params |
|---|---|---|
| OpenAI | openai/gpt-4o | api_key |
| Azure OpenAI | azure/<deployment-name> | api_key, api_base, api_version |
| Anthropic | anthropic/claude-3-5-sonnet-20241022 | api_key |
| AWS Bedrock | bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0 | AWS creds via env |
| Google Vertex | vertex_ai/gemini-1.5-pro | vertex_project, vertex_location |
| Ollama | ollama/llama3 | api_base (e.g. http://localhost:11434) |
| Groq | groq/llama-3.3-70b-versatile | api_key |
| Together AI | together_ai/meta-llama/Llama-3-70b | api_key |
| Mistral | mistral/mistral-large-latest | api_key |
Full list: https://docs.litellm.ai/docs/providers
Run
curl -s -X POST "$BASE/model/new" \
-H "Authorization: Bearer $KEY" \
-H "Content-Type: application/json" \
-d '{
"model_name": "<public-name>",
"litellm_params": {
"model": "<provider/deployment>",
"api_key": "<key>",
"api_base": "<base_if_needed>",
"api_version": "<version_if_azure>"
}
}'
Test it
After adding, verify it routes:
curl -s -X POST "$BASE/chat/completions" \
-H "Authorization: Bearer $KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "<public-name>",
"messages": [{"role": "user", "content": "say hi"}],
"max_tokens": 10
}'
Output
Show model_id from the response — needed to update or delete the model later.
Report pass/fail from the test call.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/berriai/litellm-skills/add-model">View add-model on skillZs</a>