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Found 15 Skills
OpenRouter integration. Manage data, records, and automate workflows. Use when the user wants to interact with OpenRouter data.
MCP (Model Context Protocol) 服务器构建指南
Implement LangChain rate limiting and backoff strategies. Use when handling API quotas, implementing retry logic, or optimizing request throughput for LLM providers. Trigger with phrases like "langchain rate limit", "langchain throttling", "langchain backoff", "langchain retry", "API quota".
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
Harden AI/LLM deployments against prompt injection, data exfiltration, model theft, and supply chain attacks. Covers input validation, output filtering, access control, model API security, and compliance controls for production AI systems.
OpenRouter AI integration — list available models, get integration code examples for different environments, and send prompts to any OpenRouter-compatible model. Requires OPENROUTER_API_KEY env var for chat operations.
Run application agents through SpendGuard with strict hard budget caps. Use when setting up `spendguard-sidecar`, creating agent IDs, setting or topping budgets, sending OpenAI/Grok/Gemini/Anthropic calls through SpendGuard endpoints, and troubleshooting budget enforcement errors like insufficient budget, in-flight lock conflicts, missing `x-cynsta-agent-id`, or remote pricing signature failures.
Use when managing AI Hub account, API keys, balance, usage, or API endpoints. Use when user says "AI Hub", "add AI credits", "create API key", "check AI usage", "auto-recharge", "AI Hub endpoint", "AI Hub base URL", "how to use AI Hub API", "LLM API", "AI API", "OpenAI compatible", "Anthropic API", "GPT", "Claude", "Gemini", "DeepSeek", or "Grok" in the context of Zeabur.
BYOK — register a custom LLM endpoint (Anthropic, OpenAI, Qwen, DeepSeek, etc.) with your own API key
Text analytics using LLM APIs — sentiment analysis, customer feedback classification, document entity extraction, multi-language support (English/Luganda/Swahili), feedback aggregation, and NLP feature implementation for PHP/Android/iOS. Sources...
VCR.py HTTP recording for Python tests. Use when testing Python code making HTTP requests, recording API responses for replay, or creating deterministic tests for external services.
Answer ZenMux questions by reading the latest official docs. Use for product features, APIs, integration, pricing, models/providers, routing, fallback, streaming, multimodal, structured output, tool calling, reasoning, prompt caching, image/video generation, web search, long context, observability, logs, cost tracking, subscriptions, PAYG, invoices, FAQ, privacy, terms, compliance, and tool guides for Claude Code, Cursor, Cline, Codex, Gemini CLI, opencode, Cherry Studio, Obsidian, Sider, Open-WebUI, Dify, and GitHub Copilot. Trigger on "ZenMux docs", "ZenMux API", "how to use ZenMux", "models", "pricing", "ZenMux 怎么用", "文档", "快速开始", "API 参考", "模型路由", "供应商路由", "订阅", "按量计费", "接入", "配置". Also use when ZenMux is the project context and the user asks about LLM API aggregation, model routing, or provider fallback.