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Found 1,953 Skills
Design and analyze A/B tests with proper statistical methodology including sample size calculation, randomization, frequentist and Bayesian approaches, and sequential testing. Use this skill when the user needs to set up an experiment, calculate required sample size, interpret test results, or decide between testing methodologies — even if they say 'should we A/B test this', 'how many users do we need', 'is the test result conclusive', or 'can we stop the test early'.
AscendC Operator End-to-End Development Orchestrator. Used when users need to develop new operators, implement custom operators, or complete the full process from requirements to testing. Keywords: operator development, end-to-end, full process, workflow orchestration, new operator creation.
Ascend C Code Inspection Skill. Conduct security specification inspection on code based on the hypothesis testing methodology. When calling, you must clearly provide: code snippets and inspection rule descriptions. TRIGGER when: Users request code inspection, code review, ask code security questions, check coding specifications, or need to check specific code issues (such as memory leaks, integer overflows, null pointers, etc.). Keywords: Ascend C, code inspection, code review, security specification, memory, pointer, overflow, leak, coding specification.
昇腾（Ascend）推理生态开源代码仓库智能问答专家旨在为 vLLM、vLLM-Ascend、MindIE-LLM、MindIE-SD、MindIE-Motor、MindIE-Turbo 以及 msModelSlim (MindStudio-ModelSlim) 等仓库提供专家级且易于理解的解释。在处理昇腾（Ascend）推理生态相关项目的用户询问时，务必触发此技能（Skill），可解答使用方法、部署流程、支持模型、支持特性、系统架构、配置管理、调试、测试、故障排查、性能优化、定制开发、源码解析以及其他技术问题。支持中英文双语回复，并可借助 deepwiki MCP 工具检索仓库知识库，生成具备上下文感知且基于证据的回答。Ascend inference ecosystem open-source code repository intelligent question-and-answer (Q&A) expert. Provide expert-level yet comprehensible explanations for repositories such as vLLM, vLLM-Ascend, MindIE-LLM, MindIE-SD, MindIE-Motor, MindIE-Turbo, and msModelSlim (MindStudio-ModelSlim). Use this skill when addressing user inquiries related to these Ascend inference ecosystem projects, including topics such as usage, deployment process, supported models, supported features, system architecture, configuration management, debugging, testing, troubleshooting, performance optimization, custom development, source code analysis, and any other technical issues about these projects. Support responses in both Chinese and English. Use deepwiki MCP tools to query repository knowledge bases and generate context-aware, evidence-based responses.
Guides use of ProjectDiscovery Katana for web crawling and spidering in security testing and recon workflows. Covers installation, standard vs headless mode, scope and rate limits, JSONL output, and piping from httpx or URL lists. Use when the user mentions Katana, projectdiscovery/katana, web crawling, spidering, endpoint discovery, attack surface mapping, or chaining crawlers in automation pipelines.
Automatically generate intelligent PR descriptions by analyzing code changes. Uses Git diffs, commit history, and context to create comprehensive pull request descriptions with summary, changes, testing notes, and breaking changes.
Use when the user asks about chaos engineering, fault injection, resilience testing, or HA verification for a SPECIFIC AWS service (e.g., RDS, EKS, MSK, ElastiCache, DynamoDB, S3, Lambda, OpenSearch, etc.). Triggers on "chaos testing on [service]", "fault injection for [service]", "how to test HA of [service]", "FIS scenarios/actions for [service]", "[service] failover testing", "[service] resilience testing", "[service] 混沌测试", "[service] 故障注入", "[service] 高可用验证", "对 [service] 做混沌实验", "test my [service]", "verify my [service] is resilient". Use this skill even when the user phrases it casually like "test my RDS" or "how resilient is my MSK cluster".
Application performance profiling and bottleneck identification — Node.js profiling, Chrome DevTools, flame graphs, memory leak detection, CPU profiling, React rendering performance. Activate on "profiling", "performance bottleneck", "flame graph", "memory leak", "slow app", "CPU profiling", "heap snapshot", "React re-renders", "EXPLAIN ANALYZE", "event loop lag", "clinic.js", "Core Web Vitals". NOT for infrastructure monitoring or observability (use logging-observability), load testing (use a load-testing skill), or database schema optimization.
Provides AWS CDK TypeScript patterns for defining, validating, and deploying AWS infrastructure as code. Use when creating CDK apps, stacks, and reusable constructs, modeling serverless or VPC-based architectures, applying IAM and encryption defaults, or testing and reviewing `cdk synth`, `cdk diff`, and `cdk deploy` changes. Triggers include "aws cdk typescript", "create cdk app", "cdk stack", "cdk construct", "cdk deploy", and "cdk test".
Expert bash/shell scripting system across ALL platforms. PROACTIVELY activate for: (1) ANY bash/shell script task, (2) System automation, (3) DevOps/CI/CD scripts, (4) Build/deployment automation, (5) Script review/debugging, (6) Converting commands to scripts. Provides: Google Shell Style Guide compliance, ShellCheck validation, cross-platform compatibility (Linux/macOS/Windows/containers), POSIX compliance, security hardening, error handling, performance optimization, testing with BATS, and production-ready patterns. Ensures professional-grade, secure, portable scripts every time.
Security leadership for growth-stage companies. Risk quantification in dollars, compliance roadmap sequencing (SOC 2, ISO 27001, HIPAA, GDPR), security architecture strategy, incident response leadership, vendor security assessment, and board-level security reporting. Use when building security programs, justifying security budget, selecting compliance frameworks, managing incidents, assessing vendor risk, preparing for audits, or when user mentions CISO, security strategy, compliance, zero trust, board security, risk assessment, incident response, SOC 2, ISO 27001, HIPAA, GDPR, penetration testing, or vulnerability management.
[Pragmatic DDD Architecture] Guide for creating DDD Repositories (Interfaces and Infrastructure). Use when creating repository contracts or implementing them using Drizzle ORM, Zod, and Postgres. Enforces completely typed transactions with Drizzle Transaction types (no 'unknown'), Result returns for Railway-oriented programming via neverthrow, and mapping pg node errors to domain errors. Fits our docker-compose / drizzle-kit standard testing workflow.