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Found 3,126 Skills
Use the Playwright MCP server (@playwright/mcp) for browser-driven verification, screenshots, console logs, and UI flow validation; use when debugging or validating Angular UI behavior beyond unit tests.
QA web testing skill using Chrome DevTools MCP tools for visual regression testing, responsive breakpoint validation, and CSS layout debugging. Use this skill whenever the user asks to "test a page", "check breakpoints", "verify responsive layout", "QA this page", "test CSS at different viewports", "check for layout bugs", "verify the fix", or wants to visually inspect a web page at specific viewport widths. Also triggers when the user provides a URL and asks to take screenshots, compare layouts, or inspect element dimensions. Works with any Chrome DevTools MCP-connected browser session on localhost or staging environments.
Complete bug bounty workflow — recon (subdomain enumeration, asset discovery, fingerprinting, HackerOne scope, source code audit), pre-hunt learning (disclosed reports, tech stack research, mind maps, threat modeling), vulnerability hunting (IDOR, SSRF, XSS, auth bypass, CSRF, race conditions, SQLi, XXE, file upload, business logic, GraphQL, HTTP smuggling, cache poisoning, OAuth, timing side-channels, OIDC, SSTI, subdomain takeover, cloud misconfig, ATO chains, agentic AI), LLM/AI security testing (chatbot IDOR, prompt injection, indirect injection, ASCII smuggling, exfil channels, RCE via code tools, system prompt extraction, ASI01-ASI10), A-to-B bug chaining (IDOR→auth bypass, SSRF→cloud metadata, XSS→ATO, open redirect→OAuth theft, S3→bundle→secret→OAuth), bypass tables (SSRF IP bypass, open redirect bypass, file upload bypass), language-specific grep (JS prototype pollution, Python pickle, PHP type juggling, Go template.HTML, Ruby YAML.load, Rust unwrap), and reporting (7-Question Gate, 4 validation gates, human-tone writing, templates by vuln class, CVSS 3.1, PoC generation, always-rejected list, conditional chain table, submission checklist). Use for ANY bug bounty task — starting a new target, doing recon, hunting specific vulns, auditing source code, testing AI features, validating findings, or writing reports. 中文触发词：漏洞赏金、安全测试、渗透测试、漏洞挖掘、信息收集、子域名枚举、XSS测试、SQL注入、SSRF、安全审计、漏洞报告
Deploy production recommendation systems with feature stores, caching, A/B testing. Use for personalization APIs, low latency serving, or encountering cache invalidation, experiment tracking, quality monitoring issues.
Pragmatic patterns for building multiplayer games: matchmaking, tick loops, realtime state, interest management, and validation.
.NET Testing Basic Skills Overview and Guidance Hub. Triggered when users ask general testing questions such as "How to write .NET tests", "Introduction to .NET testing", "What testing tools are needed", "Testing best practices", "Learn testing from scratch", etc. It will recommend suitable sub-skill combinations based on specific needs, covering 19 basic skills including testing fundamentals, test data, assertions, mocking, special scenarios, etc. Keywords: dotnet testing, .NET testing, testing introduction, how to write tests, testing best practices, unit test, unit testing, xunit, 3A pattern, FIRST principles, assertion, assertion, mock, stub, NSubstitute, test data, AutoFixture, Bogus, validator, FluentValidation, TimeProvider, IFileSystem, code coverage, ITestOutputHelper, test naming
Use when you need to implement or improve Java metrics observability with Micrometer — including meter design, naming/tag conventions, cardinality control, timers/counters/gauges/distribution summaries, percentiles/histograms, Actuator/Prometheus integration, and metrics validation through tests. This should trigger for requests such as Improve metrics; Apply Micrometer; Add metrics observability; Refactor Micrometer instrumentation. Part of cursor-rules-java project
Perform "Rank Reduction" on any domain — start from phenomena, extract dimensions, identify constraints, find irreducible independent generators (rank), and verify through generation tests and validation. Use when the user says "Rank Reduction", "find the rank", "what is the rank of this domain", or wants to find the irreducible principles of any domain.
Import existing Azure resources into Terraform using Azure CLI discovery and Azure Verified Modules (AVM). Use when asked to reverse-engineer live Azure infrastructure, generate Infrastructure as Code from existing subscriptions/resource groups/resource IDs, map dependencies, derive exact import addresses from downloaded module source, prevent configuration drift, and produce AVM-based Terraform files ready for validation and planning across any Azure resource type.
Learn to implement Syncfusion WinForms PercentTextBox control for collecting and displaying percentage values with validation, formatting, and data binding. Covers installation, value management, constraints, formatting options, and event handling for robust percentage input forms.
Uses Postman to perform structured API security testing by building collections that test for OWASP API Security Top 10 vulnerabilities including authentication bypass, authorization flaws, injection, and data exposure. The tester creates environments with multiple user roles, writes test scripts for automated security validation, and integrates Postman with OWASP ZAP and Newman for CI/CD security testing. Activates for requests involving Postman security testing, API security collection, automated API testing, or OWASP API testing with Postman.
Integrate a HuggingFace Computer Vision model into the NVIDIA TAO Toolkit ecosystem (tao-core config, tao-pytorch trainer, tao-deploy TensorRT pipeline). Use when the user asks to "integrate a HuggingFace model into TAO", "add an HF model to TAO Toolkit", "wire a HuggingFace ViT/DETR/ SegFormer into tao-pytorch", "build a TAO trainer + deploy pipeline for an HF CV model", or pastes a HuggingFace model URL/ID and wants it turned into a TAO model. Covers the full 7-phase loop: prerequisites check, HuggingFace inspection and validation, codebase exploration, tao-core configuration and native trainer implementation, ONNX export plus TensorRT deploy integration, packaging and L0 testing, container-based end-to-end validation, and (conditional) accuracy/latency tuning. Supports classification, object detection, semantic / instance / panoptic segmentation, zero-shot detection, and depth estimation.