'testing' 검색 결과

Use when the user asks to "optimize entity presence", "build knowledge graph", "improve knowledge panel", "entity audit", "establish brand entity", "Google does not know my brand", "no knowledge panel", or "establish my brand as an entity". Works standalone with public search and AI query testing; supercharged when you connect ~~knowledge graph + ~~SEO tool + ~~AI monitor for automated entity analysis. For structured data implementation, see schema-markup-generator. For content-level AI optimization, see geo-content-optimizer.

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Backtest crypto and traditional trading strategies against historical data. Calculates performance metrics (Sharpe, Sortino, max drawdown), generates equity curves, and optimizes strategy parameters. Use when user wants to test a trading strategy, validate signals, or compare approaches. Trigger with phrases like "backtest strategy", "test trading strategy", "historical performance", "simulate trades", "optimize parameters", or "validate signals".

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Test and assure quality — test plan, QA, coverage, unit test, integration test, end-to-end, performance, benchmark, regression. Applies TDD and FIRST principles for the CTO office's tester.

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Use this skill when the user asks to test, verify, interact with, or automate web pages and browsers. Trigger for requests involving Chrome automation, browser testing, web scraping, screenshot capture, element selection, or checking web applications. Also trigger when user mentions "browser tools" explicitly.

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Comprehensive technology-agnostic prompt generator for documenting end-to-end application workflows. Automatically detects project architecture patterns, technology stacks, and data flow patterns to generate detailed implementation blueprints covering entry points, service layers, data access, error handling, and testing approaches across multiple technologies including .NET, Java/Spring, React, and microservices architectures.

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Website exploration for testing using Playwright MCP

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End-to-end skill for building, testing, linting, versioning, and publishing a production-grade Python library to PyPI. Covers all four build backends (setuptools+setuptools_scm, hatchling, flit, poetry), PEP 440 versioning, semantic versioning, dynamic git-tag versioning, OOP/SOLID design, type hints (PEP 484/526/544/561), Trusted Publishing (OIDC), and the full PyPA packaging flow. Use for: creating Python packages, pip-installable SDKs, CLI tools, framework plugins, pyproject.toml setup, py.typed, setuptools_scm, semver, mypy, pre-commit, GitHub Actions CI/CD, or PyPI publishing.

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Find and own a defensible market position. Use when messaging sounds like competitors, conversion is weak despite awareness, repositioning a product, or testing positioning claims. Includes Crawl-Walk-Run rollout methodology and the word change that improved enterprise deal progression.

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Get best practices for JUnit 5 unit testing, including data-driven tests

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Get best practices for TUnit unit testing, including data-driven tests

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Get best practices for XUnit unit testing, including data-driven tests

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Get best practices for MSTest 3.x/4.x unit testing, including modern assertion APIs and data-driven tests

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Get best practices for NUnit unit testing, including data-driven tests

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Use when creating or updating component fixtures for screenshot testing, or when designing UI components to be fixture-friendly. Covers fixture file structure, theming, service setup, CSS scoping, async rendering, and common pitfalls.

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CI/CD pipeline patterns with GitHub Actions, release automation, and testing strategies. Use for: github actions, workflow, CI, CD, pipeline, deploy, release, semantic release, changesets, goreleaser, matrix, cache, secrets, environment, artifact, reusable workflow, composite action.

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Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.

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Autonomous iterative experimentation loop for any programming task. Guides the user through defining goals, measurable metrics, and scope constraints, then runs an autonomous loop of code changes, testing, measuring, and keeping/discarding results. Inspired by Karpathy's autoresearch. USE FOR: autonomous improvement, iterative optimization, experiment loop, auto research, performance tuning, automated experimentation, hill climbing, try things automatically, optimize code, run experiments, autonomous coding loop. DO NOT USE FOR: one-shot tasks, simple bug fixes, code review, or tasks without a measurable metric.

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Scan websites for common vulnerabilities including SQL injection, open ports, and DevTools-related issues. This skill is designed for testing user-owned websites and is compatible with OpenClaw.

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Debug REST/GraphQL APIs: status codes, auth, schemas, repro.

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TDD: enforce RED-GREEN-REFACTOR, tests before code.

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Develop Burp Suite extensions in Java (Montoya API) or Python (Jython). Supports creating HTTP listeners, scanner checks, intruder payloads, UI tabs, and context menus. Includes project templates, multi-platform setup guides, and best practices.

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Create a Beads-first refactor plan through detailed interview, repo verification, alternatives, scope boundaries, testing decisions, and tiny working increments. Use when the user wants to plan a refactor, write a refactoring RFC, or turn a risky change into safe incremental work.

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Master Temporal workflow orchestration with Python SDK. Implements durable workflows, saga patterns, and distributed transactions. Covers async/await, testing strategies, and production deployment. Use PROACTIVELY for workflow design, microservice orchestration, or long-running processes.

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You are a TypeScript project architecture expert specializing in scaffolding production-ready Node.js and frontend applications. Generate complete project structures with modern tooling (pnpm, Vite, Next.js), type safety, testing setup, and configuration following current best practices.

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