Agent skill · Backend & API

api-ai-litellm

LiteLLM proxy server setup, TypeScript client patterns via OpenAI SDK, model routing, fallbacks, load balancing, spend tracking, virtual keys, and production deployment

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill api-ai-litellm --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 17 KB
Bundled scripts: none
Path: skills/ai-llm/api-ai-litellm/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# LiteLLM Proxy Patterns > **Quick Guide:** LiteLLM is an OpenAI-compatible proxy (AI gateway) that routes requests to 100+ LLM providers. TypeScript clients connect via the standard OpenAI SDK with `baseURL` pointed at the proxy. Configure models, fallbacks, load balancing, and budgets in `config.yaml`. Use `provider/model-name` format in `litellm_params.model` (e.g., `anthropic/claude-sonnet-4-20250514`). The `model_name` in config is the user-facing alias clients request. Virtual keys require PostgreSQL. Master key must start with `sk-`. --- <critical_requirements> ## CRITICAL: Before Using This Skill > **All code must follow project conventions in CLAUDE.md** (kebab-case, named exports, import ordering, `import type`, named constants) **(You MUST use the `provider/model-name` format in `litellm_params.model` -- e.g., `anthropic/claude-sonnet-4-20250514`, `openai/gpt-4o`, `azure/my-deployment` -- the provider prefix is how LiteLLM routes to the correct API)** **(You MUST set `model_name` as the user-facing alias that clients request -- this is NOT the provider model ID, it is the name your TypeScript client passes as `model`)** **(You MUST point the OpenAI SDK `baseURL` at the p

What's inside
Steps it walks through
  1. CRITICAL: Before Using This Skill
  2. Examples Index
  3. Philosophy
  4. Core Patterns
  5. Pattern 1: Minimal config.yaml
  6. Pattern 2: TypeScript Client via OpenAI SDK
  7. Pattern 3: Fallback Chains
  8. Pattern 4: Load Balancing Across Deployments
  9. Pattern 5: Virtual Keys with Budgets
  10. Pattern 6: Spend Tracking with Tags
  11. Decision Framework
  12. Do You Need a Proxy?
  13. Which Routing Strategy?
  14. Virtual Keys vs Master Key Only
Ships with 1 file
  • metadata.json
Commands it runs
Generate a virtual key via API
curl 'http://localhost:4000/key/generate' \
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About this skill
What does the api-ai-litellm skill do?

LiteLLM proxy server setup, TypeScript client patterns via OpenAI SDK, model routing, fallbacks, load balancing, spend tracking, virtual keys, and production deployment

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill api-ai-litellm --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going