2,287 件 ・ 関連度順
概要と使いどころ
Generates optimized read queries using Dapper. Includes multi-mapping for joins, pagination, dynamic filtering, CTEs, and best practices for high-performance data access.
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。
Manipulate row selection (`df.selection`) on a Datagrok DataFrame via the datagrok_exec tool — set, clear, invert, add to, remove from, intersect, and read the selection mask. Also covers current row (`df.currentRowIdx`), the cross-skill bridges to/from the filter, and how to materialize the selected rows as a new DataFrame. Use whenever the user says "select rows", "deselect", "invert selection", "highlight rows", "selected rows", "clear selection", "current row", "currentRowIdx", "count selected", "list selected indexes", "selection from filter", "filter from selection", or asks for selected rows as a new table. Does NOT cover row filtering (separate skill `datagrok-filtering`) or generic DataFrame cloning (`datagrok-df-and-columns`).
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。
Manage WezTerm mux servers for AI agent swarms on high-RAM servers (512GB+). Use when wezterm mux unresponsive, agent sessions need rescue, tuning scrollback, or configuring persistent remote sessions.
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。
Core programming concepts from variables through recursion. Covers data types (integers, floats, strings, booleans, arrays, objects), variables and scope (lexical, dynamic, block, function, global), control flow (conditionals, loops, pattern matching), functions (parameters, return values, closures, higher-order functions), recursion (base cases, call stack, tail recursion, mutual recursion), type systems (static vs dynamic, strong vs weak, type inference, generics), and error handling (exceptions, Result types, defensive programming). Use when teaching, reviewing, or diagnosing issues with fundamental programming constructs.
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。
Systems programming from memory management through networking. Covers memory models (stack vs heap, manual allocation, garbage collection, ownership/borrowing), concurrency (threads, mutexes, channels, async/await, actor model, data races vs race conditions), operating system concepts (processes, virtual memory, page tables, system calls, file descriptors, signals), compilation (lexing, parsing, code generation, linking, static vs dynamic libraries), networking fundamentals (TCP/IP, sockets, HTTP, DNS, TLS), and the hardware-software boundary (caches, cache lines, false sharing, memory-mapped I/O). Use when working with low-level code, diagnosing system-level bugs, understanding performance characteristics, or bridging between high-level languages and machine behavior.
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。
Triggers for automatically invoking the decision-framework skill before irreversible or high-blast-radius operations. Use as a checkpoint: when a proposed action matches a trigger pattern, pause and run the appropriate framework (first-principles, inversion, decision matrix, second-order thinking) before proceeding. Prevents ad-hoc calls from becoming regret.
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。
Manages skill-creator integration with GSD workflows including skill loading, session observation, bounded learning guardrails, and pattern detection. Use this skill whenever: executing any GSD phase (to ensure relevant skills are loaded first), starting or resuming a work session (to check for pending suggestions), the user asks about skills, patterns, or skill-creator status, performing code changes that might represent repeating patterns, the user corrects Claude's output (highest-signal observation), or when skill refinement, creation, or suggestion review is discussed. Critical for maintaining the adaptive learning layer.
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。
Linear algebra and higher-dimensional thinking. Vectors, matrices, transformations — the architecture of mathematical space.
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。
Deep symmetries and unifying principles — gauge theory, Lie groups, Noether's theorem, and the Standard Model. Constructs field theories from symmetry requirements, derives conservation laws, and traces force unification. Use when working with gauge symmetry, Lie groups (U(1), SU(2), SU(3)), conservation laws via Noether's theorem, the Higgs mechanism, or Standard Model 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。
Scaffold high-fidelity UI component mockups using the project UI stack consuming approved wireframes. Use when implementing approved wireframes.
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。
字幕与花字：为带货短视频生成 ASS/SRT 字幕与花字（大标题弹出、关键词高亮、贴纸标签、行动号召按钮），自动避开平台底部/右侧 UI 安全区，并用 ffmpeg/libass 烧录。Use when the user wants subtitles, captions, 字幕, 花字, 大字报, keyword highlight, burned-in captions, SRT/ASS files, or text overlays that don't get covered by TikTok/抖音 UI.
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。
直播切片：从电商直播录屏中找出高光片段（按时间戳 / 按字幕关键词 / 按停顿自动提议），批量导出 9:16 竖屏切片，自动模糊填充横屏画面、烧录标题与字幕、响度标准化，并给切片写标题与开头钩子。Use when the user has a livestream recording and wants 直播切片, 切片, highlights, clips, 高光片段, repurpose a live stream into short videos for 抖音 / 视频号 / TikTok.
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。
Specialized hardware interfaces and system reliability for Zephyr RTOS. Covers LVGL GUI development, Audio I2S/Codecs, Watchdog timers, and Fault Injection. Trigger when building human-machine interfaces (HMI), audio devices, or high-reliability mission-critical systems.
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 should be used when the user asks to create custom Remotion transitions, asks about "cool transitions", "cinematic transitions", "striped transitions", "glitch transitions", "custom TransitionPresentation", or wants to build scene-to-scene transitions in Remotion beyond the built-in library. Also triggers for "how to make transitions in Remotion", "custom transition", "high-energy transitions", "energy transitions", "branded transitions".
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。
Create distinctive, production-grade frontend interfaces with high design quality that avoids generic AI aesthetics. Use when the task involves `build web components`, `create frontend interface`, `build web page`, `build web application`, `frontend design`, `create UI component`, or `design web interface`.
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。
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
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 git repository history to produce a codebase risk profile before code review. Probes repo size, runs 7 parallel git analysis pipelines (hotspots, bug magnets, bus factor, contributor momentum, firefighting frequency, newly added files), cross-references hotspots with bug magnets to identify high-risk files with primary owner annotation, and writes walkthrough/recon-report.md. Use before code review to prioritize reviewer attention, at the start of linear-walkthrough Phase 1 Discovery to weight file coverage, or when onboarding to an unfamiliar codebase.
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。
Runs a multi-model orchestration workflow led by the session's Fable or Claude Opus model. Sends menial tool-calling work to Haiku subagents, judgment work to Opus subagents at an effort matched to each task, and high-stakes or fresh-perspective questions to a GPT-6 Astra Codex peer. Detects the lead from session context; `--lead fable` or `--lead opus` overrides. Use to orchestrate, delegate, fan out, get a decorrelated Codex opinion, run a blind Opus-Codex cross-check, or act as tech lead.
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。
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
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。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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。
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
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。
Write modern, high-performance C# code using records, pattern matching, value objects, async/await, Span<T>/Memory<T>, and best-practice API design patterns. Emphasizes functional-style programming with C# 12+ features.
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 code coverage and CRAP (Change Risk Anti-Patterns) scores to identify high-risk code. Use OpenCover format with ReportGenerator for Risk Hotspots showing cyclomatic complexity and untested code paths.
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。