mjunaidca

Set up a FREE local LLM (via Ollama) and connect Claude Code to it so it runs offline with no API costs. Use this whenever the user wants to run Claude Code on a local/self-hosted model, use Ollama/Qwen/Llama/Mistral/DeepSeek with Claude Code, get a "free" or "offline" coding agent, avoid Anthropic API costs, point ANTHROPIC_BASE_URL at localhost, or asks "can my machine/VPS run a local LLM for Claude Code". Trigger even if they only say "run Claude Code locally", "local model for coding", "self-hosted Claude Code", or name a local model (qwen3, llama3, deepseek-coder). Handles install, model tuning, wiring, and an honest hardware reality-check (a capable model AND fast hardware are BOTH required).

Production-grade Docker containerization for Python and Node.js applications. This skill should be used when users ask to containerize applications, create Dockerfiles, dockerize projects, or set up Docker Compose. Auto-detects project structure, analyzes .env for secrets, validates security, and generates tested Dockerfiles.

Production-grade Helm 4 chart development, release management, and debugging. This skill should be used when users ask to create Helm charts, deploy with Helm, manage releases (install/upgrade/rollback), push charts to OCI registries, debug failed deployments, configure chart dependencies, create umbrella charts, set up GitOps with ArgoCD/Flux, or troubleshoot Helm issues. Auto-detects from Dockerfile/code, generates production-hardened charts with library patterns. Complements kubernetes skill.

Apache Kafka on Kubernetes with Strimzi (KRaft mode, no ZooKeeper). This skill should be used when users ask to deploy Kafka clusters, build producers/consumers, implement event-driven patterns, or debug Kafka issues. Includes tested manifests and Makefile for one-command deployment.

Production-grade Kubernetes manifests and debugging for containerized applications. This skill should be used when users ask to deploy to Kubernetes, create K8s manifests, containerize for K8s, set up Deployments/Services/Jobs/StatefulSets/CronJobs, create namespaces with resource quotas, set up multi-team isolation, configure ResourceQuota/ LimitRange, secure with RBAC (ServiceAccount, Role, RoleBinding), configure init containers (model download, db wait, migrations), set up sidecars (logging, metrics), or debug pods (CrashLoopBackOff, logs, exec, describe, events). Auto-detects from Dockerfile/code, generates hardened manifests with educational comments. CKAD-aligned.

Build evaluation frameworks for agent systems. Use when testing agent performance, validating context engineering choices, or measuring improvements over time.

Design and implement memory architectures for agent systems. Use when building agents that need to persist state across sessions, maintain entity consistency, or reason over structured knowledge.

Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.

Creates assessments with varied question types (MCQ, code-completion, debugging, projects) aligned to learning objectives with meaningful distractors based on common misconceptions. Activate when educators design quizzes, exams, or tests measuring understanding; need questions at appropriate cognitive levels (Bloom's taxonomy); want balanced cognitive distribution (60%+ non-recall); or require rubrics for open-ended questions. Generates MCQs with diagnostic distractors, code-writing prompts, debugging challenges, and project-based assessments targeting deep understanding.

Integrate OpenAI ChatKit framework with custom backend and AI agents. Handles ChatKit server implementation, React component integration, context injection, and conversation persistence.

This skill should be used when scaffolding complex concepts for learners. It applies cognitive load architecture principles to break down concepts into digestible pieces while respecting learning science limits.

Docusaurus file naming, syntax, and structure conventions for RoboLearn platform

This skill should be used when deploying a Docusaurus site to GitHub Pages. It automates the configuration, building, and deployment process, handling GitHub Pages setup, environment configuration, and CI/CD automation. Includes local validation before GitHub Actions triggering.

Design simulation worlds using SDF with ground planes, models, physics configuration, and lighting

Generate measurable learning outcomes aligned with Bloom's taxonomy and CEFR proficiency levels for educational content. Use this skill when educators need to define what students will achieve, create learning objectives for curriculum planning, or ensure objectives are specific and testable rather than vague. This skill helps break down complex topics into progressively building learning goals with clear assessment methods and success criteria.

Generate lesson content following 4-Layer Teaching Framework with standardized metadata and Docusaurus conventions

Use this skill whenever the user wants to find trading opportunities, detect arbitrage, analyze a market, perform edge detection, find mispricing, do probability analysis, evaluate orderbook depth, find momentum signals, or assess Polymarket market quality. Triggers: "find opportunities", "detect arbitrage", "analyze market", "edge detection", "mispricing", "probability analysis", "orderbook analysis", "momentum scanner", "market inefficiency", "price gap", "volume surge", "trading edge", "market analysis".

Use this skill when the user wants to execute a real trade on Polymarket, place a live order, go live, buy or sell on Polymarket, check real positions, or manage a live trading wallet. Triggers: "execute trade", "live trade", "real trade", "go live", "place order polymarket", "buy on polymarket", "sell on polymarket", "check positions", "my balance", "cancel order", "live portfolio". CRITICAL: This skill executes REAL trades with REAL money. Every trade requires explicit human confirmation before execution. Never execute autonomously.

Use this skill whenever the user wants to paper trade, simulate trades, virtual trading, demo mode, practice trading, backtest strategies, test strategy performance, use paper money, manage a virtual portfolio, track simulated P&L, or do risk-free trading on Polymarket prediction markets. Also use when the user asks about their portfolio, positions, trade history, or performance report for paper trading. This is the core trading engine — it executes simulated trades against real live Polymarket prices with zero financial risk.

Use this skill whenever the user wants trading strategy advice, trade recommendations, portfolio guidance, or prediction market analysis that leads to actionable trades. Triggers: "trading strategy", "trade recommendation", "should I buy", "should I sell", "what to trade", "portfolio advice", "prediction market strategy", "position sizing", "Kelly criterion", "risk management", "entry criteria", "exit criteria", "market edge", "expected value", "when to trade", "stop trading", "drawdown", "strategy review", "daily review", "performance analysis", "paper trading strategy", "which markets", "best opportunities".

Use this skill whenever the user wants to monitor, watch, or track Polymarket prediction market prices over time. This includes setting up price alerts, watching for significant price movements, tracking spread changes, monitoring volume spikes, or getting notified about market activity. Trigger on: monitor prices, price alert, watch market, track prices, notify me, price change, polymarket alerts, market watch, price movement, volume spike, spread monitoring, track odds, prediction market alerts, continuous monitoring, price tracker, market surveillance.

Use this skill whenever the user wants to browse, search, scan, or explore Polymarket prediction markets. This includes finding markets by topic or category, checking current prices and order books, getting market data, viewing trading volumes, looking up prediction market odds, or fetching live Polymarket data. Trigger on: polymarket, prediction market, browse markets, scan markets, market data, trading prices, order book, market odds, betting odds, event contracts, binary options, crypto prices polymarket, polymarket volume, market liquidity, polymarket search, find markets.

Scaffold a new service in this monorepo end-to-end — Dockerfile, .dockerignore, GHCR build-and-push GitHub Actions workflow, then verify by building locally, pushing, watching CI, and confirming the image landed on ghcr.io. Use this skill whenever the user wants to add a new service under `services/`, mentions "bootstrap a service", "scaffold service X", "give X a Dockerfile and CI", "set up CI for the new service", or otherwise wants to wire a fresh subdirectory of `services/` into the existing tasks-mcp / tasks-agent containerization pattern. Use it even if the user only asks for *part* of the flow (just the workflow file, just the Dockerfile) — this skill knows the whole pattern and the conventions and will produce something consistent with the rest of the repo.

Universal MCP client for connecting to any MCP server. Bundle scripts/mcp-client.py with your skill to enable dynamic tool discovery and execution without context bloat. Use when creating skills that need MCP server access.

This skill conducts discovery conversations to understand user intent and agree on approach before taking action. It should be used when the user explicitly calls /interview, asks for recommendations, needs brainstorming, wants to clarify, or when the request could be misunderstood. Prevents building the wrong thing by uncovering WHY behind WHAT.