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Found 465 Skills
Set up Jetty for the first time. Guides the user through account creation, API key configuration, and introduces runbooks — human-readable markdown files that tell an agent how to accomplish multi-step tasks with measurable outcomes. Use this skill whenever the user wants to set up, configure, or get started with Jetty — including 'set up jetty', 'configure jetty', 'jetty setup', 'get started with jetty', 'install jetty', 'connect to jetty', 'jetty onboarding', 'I am new to jetty', 'how do I start with jetty', or even just 'jetty' if they do not appear to have a token yet. Also trigger if the user mentions needing an API key for Jetty or storing their OpenAI/Gemini key in Jetty.
Reference Documentation for Jiekou AI Model Services, covering LLM API (OpenAI-compatible), Image/Video/Audio APIs, integration solutions, authentication/billing/pricing/rate limiting, and troubleshooting. Suitable for questions like "How to integrate Jiekou AI into tools such as OpenAI SDK / LangChain?" and issues like Jiekou AI request failures.
Use PAL MCP to orchestrate multiple AI models (Gemini, OpenAI, Grok, Ollama) for code reviews, debugging, planning, and CLI bridging
Use whenever the user mentions LLM prompt/prefix cache misses, cached_tokens=0, cache_read_input_tokens/cache_creation_input_tokens, prompt_cache_key, cache_control/cachePoint placement, stable prefixes, tool/schema stability, TTFT/prefill latency, OpenAI/Claude/Bedrock/OpenRouter routing, vLLM/SGLang KV reuse, or LLM cost/speed regressions on repeated long prompts. Use when reviewing LLM request shape changes: prompt text, message order, request builders, tools, schemas, response_format, provider API surface, model/router settings, agent loop structure, context compaction, or inference deployment. Use for speeding up agents only when prompt-cache stability, TTFT, or cache cost is central. Do not use for generic prompt writing, generic RAG design, token counting, or non-LLM performance.
Backend AI functionality with Vercel AI SDK v5 - text generation, structured output with Zod, tool calling, and agents. Multi-provider support for OpenAI, Anthropic, Google, and Cloudflare Workers AI. Use when: implementing server-side AI features, generating text/chat completions, creating structured AI outputs with Zod schemas, building AI agents with tools, streaming AI responses, integrating OpenAI/Anthropic/Google/Cloudflare providers, or encountering AI SDK errors like AI_APICallError, AI_NoObjectGeneratedError, streaming failures, or worker startup limits. Keywords: ai sdk core, vercel ai sdk, generateText, streamText, generateObject, streamObject, ai sdk node, ai sdk server, zod ai schema, ai tools calling, ai agent class, openai sdk, anthropic sdk, google gemini sdk, workers-ai-provider, ai streaming backend, multi-provider ai, ai sdk errors, AI_APICallError, AI_NoObjectGeneratedError, streamText fails, worker startup limit ai
Automatically announces plans, issues, and summaries out loud using TTS. Use this skill PROACTIVELY after completing major tasks like finalizing a plan, resolving an issue, or generating a summary. Each project gets a unique voice so users can identify which project is speaking from another room. Providers fallback in order (google, openai, elevenlabs, say) on rate limits.
Add new LLM model pricing entries to Langfuse's default-model-prices.json. Use when adding model prices, updating model pricing, creating model entries, adding Claude/OpenAI/Anthropic/Google/Gemini/AWS Bedrock/Azure/Vertex AI model pricing, working with matchPattern regex, pricingTiers, or model cost configuration. Covers model price JSON structure, regex patterns for multi-provider matching, tiered pricing with conditions, cache pricing, and validation rules.
Compare OpenAI Codex GPT-5.3 and code-searcher responses for comprehensive dual-AI code analysis. Use when you need multiple AI perspectives on code questions.
Unified CLI workflow for generating images and videos with Gemini, OpenAI, and Grok(xAI) via `ugen`. Use for tasks that require model discovery (`ugen models`), ordered multi-input composition (`--part text:...` and `--part image:...`), provider-specific option tuning (`--option`, `--options-json`), secure token handling (env or password prompt), and troubleshooting generation failures/timeouts.
Transcribe non-realtime speech with Alibaba Cloud Model Studio Qwen ASR models (`qwen3-asr-flash`, `qwen-audio-asr`, `qwen3-asr-flash-filetrans`). Use when converting recorded audio files to text, generating transcripts with timestamps, or documenting DashScope/OpenAI-compatible ASR request and response fields.
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.
Provides Codex CLI delegation workflows for complex code generation and development tasks using OpenAI's GPT-5.3-codex models, including English prompt formulation, execution flags, sandbox modes, and safe result handling. Use when the user explicitly asks to use Codex for complex programming tasks such as code generation, refactoring, or architectural analysis. Triggers on "use codex", "delegate to codex", "run codex cli", "ask codex", "codex exec", "codex review".