「summaries」の検索結果

Turn books, PDFs, slides, documents, web pages and text into a source-grounded knowledge base, interactive learning HTML and Markdown in English or Chinese. Use for learning, summaries, explanations, review, quizzes, relationship maps, saving reusable methodology files, retrieving or comparing accumulated methods, and applying them to a real problem. 将材料转为可追溯知识库与交互学习页，支持中英文、关系图、方法论保存/检索/比较及应用；区分材料依据、推断与外部核验。

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 data-driven scientific infographics and visual summaries

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。

Automated exploratory data analysis with statistical summaries and visualizations

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。

Discord archive: search, sync freshness, DMs, summaries, TUI, repo/release work.

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。

Prepare for Chinese wealth management client meetings with performance summaries, talking points, and relationship context. Adapted from the original client-review skill for A-share portfolios and Chinese client conventions. Triggers on "A股客户回顾", "客户会议准备", "client review China", "wealth client review", "客户回访准备", or "prepare for client meeting [client]".

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。

Generates user-facing usage statistics, activity summaries, and personalized insights dashboards (weekly recaps, year-in-review, Spotify Wrapped-style). Use when user wants to show usage stats, activity insights, or shareable recap screens. Different from analytics-setup which sends data to a backend — this shows insights to the USER on-device.

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。

The cellxgene data portal (https://cellxgene.cziscience.com/) provides a graphical user interface to collections of single-cell sequence data processed in standard ways to 'count matrix' summaries. The cellxgenedp package provides an alternative, R-based inteface, allowind data discovery, viewing, and downloading.

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 knowledge for Azure AI Video Indexer development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring live camera analysis, custom AI insights, OpenAI summaries, Video Indexer APIs, or face redaction, and other Azure AI Video Indexer related development tasks. Not for Azure AI Vision (use azure-ai-vision), Azure AI Search (use azure-cognitive-search).

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。

Cooperatively pause unfinished work in the current session, leave a precise continuation checkpoint, and resume from it when the user later says continue. Use only when the user explicitly requests this pause workflow. Do not use for crashes, app shutdown, new-session handoffs, or ordinary task summaries.

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 a concise continuation prompt that a fresh agent session can paste in to resume a long or degraded session. Use when the user asks for a handoff prompt, restart prompt, continuation prompt, context transfer, fresh-session resume, or a compact summary for opening a new session. Do not use for ordinary summaries, task-forest maintenance, durable user-profile updates, automatic session creation, code execution, or external publishing.

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 this skill when the user wants an evidence-based research memo, literature review, market/policy/technical landscape, or a multi-source decision brief with citations, trade-offs, and a clear conclusion. Best for tasks that need synthesis across multiple external sources, iterative follow-up research, or a reusable written artifact. Do not use for quick factual lookups, single-source summaries, simple Q&A, summarizing one document the user already provided, plan-only requests where the user explicitly defers the actual research, or when the user wants a short answer with no need for cited evidence (a short but evidence-backed conclusion is still a brief memo, which this skill covers). Chinese trigger examples: "帮我调研", "深度研究", "综述报告", "技术选型分析", "竞品研究", "政策分析".

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。

Formats plain text or markdown files with frontmatter, titles, summaries, headings, bold, lists, and code blocks. Use when user asks to "format markdown", "beautify article", "add formatting", or improve article layout. Outputs to {filename}-formatted.md.

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。

Conducts hypothesis-driven, evidence-preserving threat hunts with bounded negative conclusions and telemetry-gap handling. Use for hunt hypotheses, scoped offline analysis, or analytic follow-up; not unscoped scanning, malware execution, or generic intelligence summaries.

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 this skill when the user uploads Excel (.xlsx/.xls) or CSV files and wants to perform data analysis, generate statistics, create summaries, pivot tables, SQL queries, or any form of structured data exploration. Supports multi-sheet Excel workbooks, aggregation, filtering, joins, and exporting results to CSV/JSON/Markdown.

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。

Conduct multi-round deep research on any GitHub Repo. Use when users request comprehensive analysis, timeline reconstruction, competitive analysis, or in-depth investigation of GitHub. Produces structured markdown reports with executive summaries, chronological timelines, metrics analysis, and Mermaid diagrams. Triggers on Github repository URL or open source 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。

Remove repeated boilerplate across sections (methodology disclaimers, generic transitions, repeated summaries) while preserving citations and meaning.

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。

Route an unbound research Goal to one Workflow or materialize its initial C0 kickoff block; use during initial binding, not for later checkpoint summaries or approval.

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。

Extract per-subsection “anchor facts” (NO PROSE) from evidence packs so the writer is forced to include concrete numbers/benchmarks/limitations instead of generic summaries.

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。

Capture a full DevTools-protocol trace of any browser automation — CDP firehose, screenshots, and DOM dumps — then bisect the stream into per-page searchable buckets. Use when the user wants to debug a failed run, audit network/console/DOM activity, attach a trace to an in-progress session, or feed structured per-page summaries back into an agent loop so its next iteration learns from the last one.

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。

Diagnose MSBuild build performance bottlenecks using binary log analysis. USE FOR: identifying why builds are slow by analyzing binlog performance summaries, detecting ResolveAssemblyReference (RAR) taking >5s, Roslyn analyzers consuming >30% of Csc time, single targets dominating >50% of build time, node utilization below 80%, excessive Copy tasks, NuGet restore running every build. Covers timeline analysis, Target/Task Performance Summary interpretation, and 7 common bottleneck categories. Use after build-perf-baseline has established measurements. DO NOT USE FOR: establishing initial baselines (use build-perf-baseline first), fixing incremental build issues (use incremental-build), parallelism tuning (use build-parallelism), non-MSBuild build 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。

Guide for interpreting ResolveProjectReferences time in MSBuild performance summaries. Activate when ResolveProjectReferences appears as the most expensive target and developers are trying to optimize it directly. Explains that the reported time includes wait time for dependent project builds and is misleading. Guides users to focus on task self-time instead. Do not activate for general build performance -- use build-perf-diagnostics instead.

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 the user is investigating QML / Qt Quick performance — both vague complaints ("the UI feels laggy", "this is slow", "frames are dropping", "the app stutters") and explicit asks to profile, find hotspots, or optimize bindings, signals, or rendering. Runs qmlprofiler on a 2D QML application, parses the .qtd trace, and analyzes hotspots against the source with frame-time, memory, and pixmap-cache summaries. Does NOT cover Qt Quick 3D.

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 concise executive summaries from detailed analysis. Use when preparing board decks, executive briefings, or condensing complex analysis into decision-ready formats for senior audiences.

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。

Performs deep AI-powered analysis and understanding of long-form videos (up to 3 hours, 10GB) using Volcengine LAS large language models. Video analysis, video comprehension, and video summarization — generates comprehensive video summaries, video recaps, chapter breakdowns, event timelines, key moments, and structured content indexing. Supports behavior detection, action detection, video annotation, video tagging, and video content recognition. Enables intelligent video question answering — ask questions about video content and get AI answers. Handles long meeting recordings, lecture videos, webinars, surveillance and security footage, movies, tutorials, and any long video that needs detailed understanding. Async processing with submit-poll workflow. Use this skill when the user wants to analyze or understand long videos (up to 3h/10GB) with LLM-based deep comprehension, summarize video content or generate recaps, extract chapters/key moments/timelines from videos, do video Q&A (ask questions about video content), detect actions/behaviors in videos, review meeting recordings/lectures/webinars, or get structured video descriptions.

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。