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Found 335 Skills
Guides architects on when and how to use goal-seeking agents as a design pattern. This skill helps evaluate whether autonomous agents are appropriate for a given problem, how to structure their objectives, integrate with goal_agent_generator, and reference real amplihack examples like AKS SRE automation, CI diagnostics, pre-commit workflows, and fix-agent pattern matching.
Comprehensive Windows 11 system diagnostics via PowerShell. Diagnoses crashes, freezes, reboots, BSOD, disk health, memory issues, hardware errors, and performance problems. Use when troubleshooting Windows stability issues, analyzing Event Viewer logs, checking disk/memory health, investigating hardware errors, or diagnosing system performance problems.
Debugs Windows applications using WinDbg and crash dump analysis including MCP server integration, live process attach, dump file triage, hang detection, high-CPU diagnosis, memory leak investigation, kernel debugging, symbol configuration, scenario command packs, diagnostic report generation, and SOS extension workflows for .NET runtime inspection.
Generate tiered knowledge-verification questions (quiz/exam) at 3 difficulty levels with grading and diagnostics. For testing UNDERSTANDING of code, concepts, or architecture — NOT for writing software tests (use engineering:testing-strategy for that). Triggers on "문제 만들어", "quiz", "검증 문제", "이해도 확인", "knowledge check", "challenge me", "시험 문제", "면접 문제".
codeck entry point. Scans local files for materials, shows pipeline dashboard with diagnostic intelligence, guides user to the next step. Use when the user says "codeck", "new deck", "make a presentation", "make a deck", "new slides", "build a presentation", or wants to start a new presentation project from scratch. Do NOT trigger for specific sub-tasks like designing, reviewing, exporting, or writing speeches — those have dedicated skills.
Helps engineering managers understand and act on what drives each engineer — produces a three-driver framework (Growth, Connection, Impact), techniques for identifying someone's primary driver, driver-aligned delegation patterns, and a team composition diagnostic. Use when the user says "this person isn't motivated," "nobody picks up tasks," "I keep reminding people," "what drives my engineers," "how do I motivate my team," "what should I delegate to this person," "engineer seems disengaged," or "what growth activity should I give this person." Do NOT use when someone is actively leaving or at risk of quitting (use retaining-developers) or when the engineer is a high performer with specific management challenges (use managing-high-performers).
ARK-style single-stock disruptive-innovation diagnostic. Suitability gate on 4 dimensions (platform fit / innovation revenue / R&D intensity / management vision); if it passes, builds TAM (low/base/high), Wright's-Law cost curve with sourced learning rate, three-scenario 5-year target (Bull/Base/Bear, 15% discount), risks, conditional action frame. Data: Longbridge CLI first, MCP fallback, WebSearch only for TAM / learning rates / industry runway. Runs cross-statement reconciliation BEFORE analysis. Closes with a data-source appendix whose final row is the reconciliation summary. Independent implementation — not affiliated with ARK Invest. Triggers: "木头姐", "ARK", "ARKK", "颠覆式创新", "莱特定律", "TAM", "5年目标价", "情景分析", "AI 与大数据", "自动化与机器人", "能源存储", "基因革命", "区块链与金融科技", "木頭姐", "顛覆式創新", "萊特定律", "5年目標價", "Cathie Wood", "ARK Invest", "disruptive innovation", "Wright's Law", "learning rate", "bull base bear", "scenario analysis".
Linux network tools and diagnostics
Run ACB (Anypoint Code Builder) system diagnostics to check if the machine meets minimum specifications and apply Windows optimizations if needed
Selects, deploys, and customizes AI models on Amazon SageMaker. Fine-tuning (SFT, DPO, RLVR, RLAIF), model selection, dataset preparation, evaluation, deployment to SageMaker endpoints or Bedrock, and endpoint diagnostics. Covers the full lifecycle from planning through production. Use when fine-tuning models on SageMaker, selecting base models from SageMaker Hub, finding a model to deploy without fine-tuning, transforming datasets for training, checking data readiness, evaluating model quality, deploying to endpoints, setting up IAM roles and S3 buckets for training jobs, or managing a SageMaker Managed MLflow app. Also use to check endpoint health, diagnose failures, debug latency or errors, or view container logs and CloudWatch metrics. Covers Serverless Model Customization, Nova and OSS deployment paths, and PySDK v3 usage. NOT for Ground Truth labeling, Feature Store, or general-purpose AWS infrastructure.
Execute deterministic, reproducible historical backtests from a start date, end date, and strategy concept using the Alpaca CLI plus agent-written workspace code. Use when the user wants to backtest a strategy, simulate historical trades, or return trades, diagnostics, and reproducibility artifacts.
AI-native tutor and onboarding workflow for the MCPA (Model Context Protocol Associate) certification in AI Engineering from Scratch. Use when a learner wants to prepare for the MCPA, resume their certification path, learn the next lesson interactively, run and verify practical labs, take the diagnostic or a full mock, or remediate weak exam domains from GitHub with Claude Code, Codex, ChatGPT, Cursor, or another agent.