Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add BerriAI/litellm-skills --skill add-modelgit clone --depth 1 https://github.com/BerriAI/litellm-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/berriai/litellm-skills/add-model)<a href="https://agentmods.dev/skills/berriai/litellm-skills/add-model"><img src="https://agentmods.dev/badge/skills/berriai/litellm-skills/add-model/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/berriai/litellm-skills/add-model"><img src="https://agentmods.dev/badge/skills/berriai/litellm-skills/add-model.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00074 | $0.00773 |
| Opus 5 | $0.00037 | $0.00387 |
| Sonnet 5 | $0.00015 | $0.00155 |
| Haiku 4.5 | $0.00007 | $0.00077 |
Grade A, and why
add-model scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
compatibility: Requires curl. How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Add Model
Add a new LLM to a live LiteLLM proxy.
Setup
Ask for these if not already known:
LITELLM_BASE_URL — e.g. https://my-proxy.example.com
LITELLM_API_KEY — proxy admin key
API reference: https://litellm.vercel.app/docs/proxy/model_management
Ask the user
- Public model name — what callers will send in
"model": "..."(e.g.gpt-4o,my-claude,llama3) - Provider — pick from the table below
- Credentials — whatever that provider needs
Provider table
| Provider | litellm_params.model |
Extra params |
|---|---|---|
| OpenAI | openai/gpt-4o |
api_key |
| Azure OpenAI | azure/<deployment-name> |
api_key, api_base, api_version |
| Anthropic | anthropic/claude-3-5-sonnet-20241022 |
api_key |
| AWS Bedrock | bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0 |
AWS creds via env |
| Google Vertex | vertex_ai/gemini-1.5-pro |
vertex_project, vertex_location |
| Ollama | ollama/llama3 |
api_base (e.g. http://localhost:11434) |
| Groq | groq/llama-3.3-70b-versatile |
api_key |
| Together AI | together_ai/meta-llama/Llama-3-70b |
api_key |
| Mistral | mistral/mistral-large-latest |
api_key |
Full list: https://docs.litellm.ai/docs/providers
Run
curl -s -X POST "$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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 84 lines · 74 tokens per session scan A 856febaf8330
add-model is a skill published in the GitHub repository BerriAI/litellm-skills (84 stars, last pushed 4mo ago), licensed MIT. It adds 74 tokens to every session and 773 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
gemini-api-agent-platform
Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK for enterprise AI applications. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.
open-source
Documentation reference for writing Python code using the browser-use open-source library. Use this skill whenever the user needs help with Agent, Browser, or Tools configuration, is writing code that imports from browseruse, asks about @sandbox deployment, supported LLM models, Actor API, custom tools, lifecycle…
deepstream-sop
Use this skill when building, deploying, evaluating, debugging, or measuring latency for the DeepStream SOP Inference Microservice — a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via event boundary detection (GEBD) plus VLM classification. Trigger even if the…
gemini-api-dev
Use this skill when writing code that calls the Gemini API for text generation, multi-turn chat, multimodal understanding, image generation, video generation, streaming responses, background research tasks, function calling, structured output, or migrating from the old generateContent API. Covers SDK usage and best…
azure-search-documents-dotnet
Azure AI Search SDK for .NET (Azure.Search.Documents). Use for building search applications with full-text, vector, semantic, and hybrid search. Covers SearchClient (queries, document CRUD), SearchIndexClient (index management), and SearchIndexerClient (indexers, skillsets). Triggers: "Azure Search .NET"…
azure-search-documents-ts
Build search applications using Azure AI Search SDK for JavaScript (@azure/search-documents). Use when creating/managing indexes, implementing vector/hybrid search, semantic ranking, or building agentic retrieval with knowledge bases.