「window」の検索結果

Use when 用户希望在 macOS 或 Windows 安装、制作、应用、暂停、恢复或设置 HeiGe Codex Desktop 皮肤常驻，或给腾讯 CodeBuddy 桌面端（WorkBuddy）一次性换肤。

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。

Manual QA harness for the senpi coding agent itself. MUST USE after changing packages/ai, packages/agent, packages/coding-agent, or packages/tui — a green typecheck and `npm test` are NOT QA. Drives the real CLI from source in an isolated sandbox (never touches ~/.senpi or real credentials) across four channels: remote RPC (--mode rpc JSONL stdio), TUI smoke (node-pty on Windows, tmux on POSIX), mock loop (a local fake model server for deterministic, zero-token agent-loop runs), and CLI smoke (--help/--print/--list-models). Every helper ships a --self-test. Use whenever someone says qa senpi, test the agent, verify my change, rpc qa, tui qa, mock-loop qa, smoke the cli, or needs evidence that an agent-loop, tool, keybinding, or provider change works end to end. Capture evidence to local-ignore/qa-evidence/.

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 a kernel dump reports a Windows bugcheck; decode parameters and recover exception or trap context before investigating your driver. Not for user-mode process crashes or blaming a module from its name alone.

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 configuring, repairing, planning, or running MiniMax H3 locally on a Windows NVIDIA computer, especially when installation compatibility, component sets, resolution, generation-time budget, path, low-VRAM risk, or H3 prompt mode must be chosen from hardware and user requirements.

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 a database schema or data-meaning change needs Parallel Change, including expand, migrate, and contract sequencing for column renames, type or data reinterpretation, large-table backfills, relationship-table changes, enum/status transitions, timezone/default changes, and index or uniqueness changes. This should trigger before framework-specific Flyway implementation guidance when deciding whether a migration needs a compatibility window or whether a simpler migration is sufficient. Part of Plinth Toolkit

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 building iOS apps with xtool (Xcode-free iOS development), creating xtool projects, adding app extensions, or configuring xtool.yml. Triggers on "xtool", "SwiftPM iOS", "iOS on Linux", "iOS on Windows", "Xcode-free", "app extension", "widget extension", "share extension". Covers project setup, app extensions, and deployment.

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 to update terminal window title with context. Triggers automatically at session start via hook. Also triggers on topic changes during conversation (debugging to docs, frontend to backend). Updates title with emoji + project + current topic.

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。

Designs multiscale chunking for RAG by embedding small units for retrieval precision and returning larger context for synthesis. Use when fixed-size chunks either lose surrounding context or dilute relevance in long documents, manuals, filings, or codebases. Covers sentence-window and parent-child or auto-merging strategies, base chunk sizing, and evaluation. Do not use when a single chunk scale already meets retrieval and generation needs.

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。

Coder-agent working-file budget discipline: keep the editable working set (files you /add into writable context) under ~25k tokens, separate "read" from "edit", delegate breadth to a read-only repo-map, and drop files once edited. Use when an LLM coder-agent edits multiple files, when the working set must stay focused, or when the model starts editing the wrong file / missing targets because too much context dilutes attention. Search keywords: context window full, agent edits wrong file, too much context, /add /drop files, working file budget, context dilution, lost in the middle.

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。

Treat the current session and auto-resume in a new terminal window.

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 Claude Code session bloat — shows token count, context usage %, and bloat breakdown. Use when the user asks about session size, context usage, or when you notice the context window is getting full.

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。

Research a specific CVE or vulnerability disclosure end-to-end — what version is affected, is your code reachable, is there a public PoC, is there a patch, what's the exposure window, what's the mitigation if you can't patch immediately. Use when the user mentions 'CVE,' 'vulnerability research,' 'is this CVE relevant,' 'zero-day,' 'CISA KEV,' 'GitHub Security Advisory,' 'reachability analysis,' 'patch analysis,' 'exploit availability,' 'EPSS,' 'CVSS,' or 'should we drop everything and patch this.'

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。

Electron desktop apps with React, TypeScript, and Vite. Use for IPC, window/tray, PTY terminals, WebRTC, and packaging.

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。

Wash sale detection under 2025 US crypto rules with 61-day window monitoring, disallowed loss tracking, and safe re-entry countdown

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 maintaining the MassGen model and backend registry. This skill should be used when adding new models, updating model information (release dates, pricing, context windows), or ensuring the registry stays current with provider releases. Covers both the capabilities registry and the pricing/token manager.

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。

Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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。

PostgreSQL-specific development assistant focusing on unique PostgreSQL features, advanced data types, and PostgreSQL-exclusive capabilities. Covers JSONB operations, array types, custom types, range/geometric types, full-text search, window functions, and PostgreSQL extensions ecosystem.

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 attacking a Windows Active Directory domain — Kerberos roasting/delegation, coercion + NTLM/Kerberos relay (CVE-2025-33073), ADCS ESC1-16 (EKUwu), ticket forgery & DCSync, dMSA BadSuccessor (CVE-2025-53779), BloodHound attack-path enumeration, domain dominance

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 hunting threats or engineering detections — ATT&CK Detection-Strategies, Sigma + correlation with Detection-as-Code CI, Windows endpoint hunting (Sysmon/ETW/LSASS/LOLBins), network C2 hunting (JA4+, beaconing, DNS tunneling), cloud-identity hunting, Atomic Red Team purple-team validation

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 turning a memory-corruption bug into a working PoC — stack/ROP, glibc heap & FSOP, format strings, browser/JIT type confusion & UAF, Linux/Windows kernel LPE against ASLR/DEP/CFG/CET/V8-Sandbox

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 designing event-driven workflows, decoupling services, implementing fan-out patterns (one trigger, many downstream handlers), implementing idempotent event handling with IDs (24-hour dedupe window), or handling at-least-once delivery from external sources like Stripe webhooks. Covers Inngest event schema, payload format, naming conventions, IDs for idempotency, the ts param, fan-out patterns, and system events like inngest/function.failed.

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。

Fast in-memory DataFrame with lazy evaluation, parallel execution, Arrow backend. Use for tabular data in RAM (1–100 GB) when pandas is too slow. Expression API: select, filter, group_by, joins, pivots, window. Lazy mode enables predicate/projection pushdown. Reads CSV, Parquet, JSON, Excel, DBs, cloud. Larger-than-RAM: Dask; GPU: cuDF.

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。

Pure Python DICOM for medical imaging (CT, MRI, X-ray, ultrasound). Read/write DICOM, pixels as NumPy, edit tags, windowing (VOI LUT), PHI anonymization, build DICOM, series→3D volumes. Use histolab for WSI pathology; nibabel for NIfTI.

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。

Operational knowledge for the daily-brief digest pipeline (this project). RSS/API fetchers, pluggable LLM enrichment (default claude CLI on Max; also anthropic/openai/deepseek/minimax API), trading section, HTML rendering, cross-platform scheduler integration (Windows Task Scheduler / macOS launchd / Linux cron). Load when the user asks about running daily / regenerating sections / debugging a failed run / adding or disabling sources / LLM quota / scheduler / why a tab shows wrong data / why a source failed / switching LLM backend. Always prefer the documented npm commands over re-implementing logic. Diagnose by reading logs/daily-*.log first, then logs/llm-calls.jsonl for LLM-side issues.

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。