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Found 1,683 Skills
OpenGame is an open-source agentic framework for end-to-end web game creation from a single text prompt, using LLMs, Game Skill (Template + Debug), and headless browser evaluation.
Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding.
Detects prompt injection using regex signature matching, heuristic scoring for structural anomalies, and DeBERTa-based transformer classification, flagging direct injections (system-prompt overrides, role-play escapes) and indirect injections (encoded payloads, obfuscation) per OWASP LLM Top 10 (LLM01:2025). Use for input validation layers in chatbots/agents/RAG pipelines, or for retrospectively classifying injection attempts in logs or incident investigations.
Reduce a webpage to a structural skeleton with semantic tokens. Two-phase pipeline: Phase 1 injects a browser script that tokenizes content ({TEXT}, {HEADING:n}, {IMAGE:WxH}, {CTA:label}, {LINK:label}, {INPUT:type}, {VIDEO}, {ICON}). Phase 2 applies LLM structural reasoning to collapse repeated patterns ({REPEAT:N}), remove decorative wrappers, strip utility classes, and produce skeleton.html + manifest.json. Use when migrating pages to EDS, analyzing page structure, extracting page blueprints, or preparing input for GenAI block generation. Triggers on: reduce page, page skeleton, page blueprint, extract structure, tokenize page, page reduction, structural skeleton, reduce URL.
Full three-perspective audit of an existing website from one URL — design (tensions + concrete improvement opportunities), SEO/technical, and LLM/AI-search visibility — plus Core Web Vitals, synthesized into a scored, evidence-bound report. Use when the user asks to "audit this site", "site audit", "design audit", "SEO audit", "why is my site underperforming", "LLM visibility", "how does my site look to AI", or invokes /stardust:audit <url>.
Implement a task with automated LLM-as-Judge verification for critical steps
Huawei Cloud Ascend model deployment and testing skill for large language models on Ascend DevServer (910B series). Supports single-machine and dual-machine deployment for LLM, VL (vision-language), Embedding, and Rerank models. Provides model inference testing, deployment log viewing, and status monitoring with automated model matching and deployment script generation. Use this skill when the user wants to: (1) deploy a model on Ascend DevServer, (2) test model inference, (3) view deployment logs or status, (4) list supported models, (5) check deployment prerequisites. Trigger: deploy, test, model list, deployment log, Ascend, DevServer, 910B, ModelArts, LLM, VL, Embedding, Rerank, multimodal, inference, model catalog, 昇腾, 部署模型, 测试模型, 模型列表, 部署日志, 模型部署, 推理测试
Delegate a coding task to Aider (`aider`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Aider - phrasings like "have Aider do X", "delegate this to aider", "run it through Aider", or "use Aider to implement/fix/refactor" - or wants to run a queue of coding tasks through Aider while staying the reviewer. This includes asking Aider to drive a local or self-hosted OpenAI-compatible endpoint ("have Aider use my local model", "run Aider against llama.cpp / Ollama / vLLM / LM Studio"), which Aider reaches via `--api-base`. DO NOT USE for local-model or coding requests that do not name Aider, for tasks small enough to do inline, or when the user wants the code written directly without delegating.
Analyze a Karpathy-pattern LLM wiki knowledge base and generate an interactive knowledge graph with entity extraction, implicit relationships, and topic clustering.
Build AI agents with structured access to Sanity content via Sanity Context. Use when setting up a Sanity-powered chatbot, connecting an AI assistant to Sanity content, or adding client-side tools to an agent. Covers Studio setup, agent implementation, and advanced patterns. Always use this skill when users mention building a chatbot with Sanity, creating an AI assistant for their content, setting up the Sanity Context MCP server, integrating Sanity with Claude/GPT/any LLM, making content searchable by AI, implementing semantic search over Sanity data, or connecting their CMS to an AI agent.
Quickly test and compare LLM models via OpenRouter. Find the fastest/cheapest model, compare response quality. Trigger words: openrouter, test model, compare models, find fastest model, find cheapest model
Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.