「understanding」の検索結果

Draft a client proposal — "write a proposal for", "draft a proposal", "turn this brief into a proposal". Produces executive summary, understanding of their problem, approach, scope, and pricing.

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Enable code intelligence (go-to-definition, find-references, hover, type info) for any programming language by installing and configuring an LSP server for Copilot CLI. Detects the OS, installs the right server, and generates the JSON configuration (user-level or repo-level). Use when you need deeper code understanding and no LSP server is configured, or when the user asks to set up, install, or configure an LSP server.

日本語の概要は準備中です。原文の説明を表示しています。

Use when feature flag tests fail, flags need updating, understanding @gate pragmas, debugging channel-specific test failures, or adding new flags to React.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-*.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating user timing marks.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze Azure resource groups and generate detailed Mermaid architecture diagrams showing the relationships between individual resources. Use this skill when the user asks for a diagram of their Azure resources or help in understanding how the resources relate to each other.

日本語の概要は準備中です。原文の説明を表示しています。

Modify, debug, or extend the s6-overlay supervision tree inside the Hermes Agent Docker image — adding new services, debugging profile gateways, understanding the Architecture B main-program pattern.

日本語の概要は準備中です。原文の説明を表示しています。

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

日本語の概要は準備中です。原文の説明を表示しています。

OpenAI's model connecting vision and language. Enables zero-shot image classification, image-text matching, and cross-modal retrieval. Trained on 400M image-text pairs. Use for image search, content moderation, or vision-language tasks without fine-tuning. Best for general-purpose image understanding.

日本語の概要は準備中です。原文の説明を表示しています。

Expert reverse engineer specializing in binary analysis, disassembly, decompilation, and software analysis. Masters IDA Pro, Ghidra, radare2, x64dbg, and modern RE toolchains. Handles executable analysis, library inspection, protocol extraction, and vulnerability research. Use PROACTIVELY for binary analysis, CTF challenges, security research, or understanding undocumented software.

日本語の概要は準備中です。原文の説明を表示しています。

This skill provides symbol-level code understanding and navigation using Language Server Protocol (LSP). Enables IDE-like capabilities for finding symbols, tracking references, and making precise code edits at the symbol level.

日本語の概要は準備中です。原文の説明を表示しています。

.NET unit test fundamentals and FIRST principles specialized skill. Used when creating unit tests, understanding testing basics, learning 3A Pattern, and mastering testing best practices. Covers FIRST principles, AAA Pattern, Fact/Theory, testing pyramid, etc. Keywords: unit test, unit test, unit testing, test fundamentals, testing fundamentals, FIRST principle, FIRST principle, 3A pattern, AAA pattern, Arrange Act Assert, Fact, Theory, InlineData, how to write tests, testing best practices, create unit test

日本語の概要は準備中です。原文の説明を表示しています。

Complete guide for upgrading xUnit 2.9.x to 3.x. Use when upgrading xUnit v2 to v3 or understanding xUnit v3 new features and breaking changes. Covers package updates, async void fixes, IAsyncLifetime adjustments. Includes new features: Assert.Skip, Explicit Tests, Matrix Theory, Assembly Fixtures. Keywords: xunit upgrade, xunit v3, xunit 3.x, xunit migration, xunit upgrade, xunit.v3, OutputType Exe, IAsyncLifetime v3, Assert.Skip, SkipUnless, SkipWhen, Explicit attribute, MatrixTheoryData, AssemblyFixture, breaking changes

日本語の概要は準備中です。原文の説明を表示しています。

This skill outlines methodologies for performing authorized penetration testing against AWS, Azure, and GCP cloud environments. It covers understanding the shared responsibility model for testing scope, leveraging cloud-specific attack tools like Pacu and ScoutSuite, exploiting IAM misconfigurations, testing for SSRF to cloud metadata services, and reporting findings aligned to MITRE ATT&CK Cloud matrix.

日本語の概要は準備中です。原文の説明を表示しています。

Low-level keylogger architecture design: kernel driver hooks (WH_KEYBOARD_LL, SetWindowsHookEx), ETW-based input capture, user-mode vs kernel-mode approaches, stealth techniques, and data exfiltration. Use for understanding input capture mechanisms, EDR evasion research, or malware architecture analysis.

日本語の概要は準備中です。原文の説明を表示しています。

iOS HealthKit data sync CLI commands and patterns. Use when working with healthsync CLI, fetching Apple Health data (steps, heart rate, sleep, workouts), pairing iOS devices over local network, or understanding the iOS Health Sync project architecture including mTLS certificate pinning, Keychain storage, and audit logging.

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Intelligently organizes files and folders by understanding context, finding duplicates, and suggesting better organizational structures. Use when user wants to clean up directories, organize downloads, remove duplicates, or restructure projects.

日本語の概要は準備中です。原文の説明を表示しています。

Browser automation powers web testing, scraping, and AI agent interactions. The difference between a flaky script and a reliable system comes down to understanding selectors, waiting strategies, and anti-detection patterns. This skill covers Playwright (recommended) and Puppeteer, with patterns for testing, scraping, and agentic browser control. Key insight: Playwright won the framework war. Unless you need Puppeteer's stealth ecosystem or are Chrome-only, Playwright is the better choice in 202

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Navigate and understand codebases using agentlens hierarchical documentation. Use when exploring new projects, finding modules, locating symbols in large files, finding TODOs/warnings, or understanding code structure.

日本語の概要は準備中です。原文の説明を表示しています。

Expert in temporal event detection, spatio-temporal clustering (ST-DBSCAN), and photo context understanding. Use for detecting photo events, clustering by time/location, shareability prediction, place recognition, event significance scoring, and life event detection. Activate on 'event detection', 'temporal clustering', 'ST-DBSCAN', 'spatio-temporal', 'shareability prediction', 'place recognition', 'life events', 'photo events', 'temporal diversity'. NOT for individual photo aesthetic quality (use photo-composition-critic), color palette analysis (use color-theory-palette-harmony-expert), face recognition implementation (use photo-content-recognition-curation-expert), or basic EXIF timestamp extraction.

日本語の概要は準備中です。原文の説明を表示しています。

Master of text-based visual communication using ASCII art, Unicode box-drawing, and structured diagram notation. Creates clear, maintainable diagrams for systems, processes, hierarchies, relationships, and psychological structures. Proactively generates diagrams to enhance understanding. Activate on visualization needs, system architecture, process flows, psychological mapping, or when complex concepts would benefit from visual representation. NOT for photo editing, vector graphics, or GUI-based design tools.

日本語の概要は準備中です。原文の説明を表示しています。