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概要と使いどころ
Maintain an existing Proto UI Prototype or implement a governed Base or design-language component slice. Use for governed component behavior, anatomy, inheritance, exports, CLI registration, style projection, demos, or public preview work. Do not use to admit a new semantic subject or invent Base ownership from a component name.
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。
Reproduce and repair a bounded Proto UI regression whose expected behavior and owning layer are already governed. Use this before domain implementation skills whenever work starts from a reproducible failure, including bug fixes, drift repairs, broken exports, Runtime failures, Adapter parity defects, Prototype defects, or public-projection regressions. Do not use when expected semantics or ownership is unresolved.
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。
Fix silent metadata issues in RFDB node storage. Covers two traps: (1) metadata flattening — nested metadata fields become top-level after serialization, so node.metadata.field is undefined but node.field works. (2) reserved keys — fields named "type", "id", "name", "file", "exported" are silently stripped from metadata by _parseNode() to prevent overwriting top-level node fields.
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 standardized charts and visual assets from analytics query results. Prefer dependency-free plain HTML/CSS/JavaScript/SVG for interactive exploratory charts; use local plotting tools such as matplotlib, seaborn, or Plotly when static/report-ready exports or specialized charting libraries are more appropriate. Use for trends, comparisons, distributions, report assets, CSV-to-chart work, and presentation-ready data visuals.
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。
Act as an interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse Cloud).
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 standardized charts and visual assets from analytics query results. Prefer dependency-free plain HTML/CSS/JavaScript/SVG for interactive exploratory charts; use local plotting tools such as matplotlib, seaborn, or Plotly when static/report-ready exports or specialized charting libraries are more appropriate. Use for trends, comparisons, distributions, report assets, CSV-to-chart work, and presentation-ready data visuals.
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。
Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.
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。
Act as an interactive data analyst for ClickHouse-backed analytics. Use when the user asks questions about internal data, metrics, dashboards, telemetry, active users, revenue, funnels, trends, distributions, or wants an analyst-style conversation, ad hoc SQL, charts, or a data export against ClickHouse (local or ClickHouse Cloud).
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。
Compress any conversation into a portable JSON context graph for handoff to a new chat or LLM. Trigger on: "compress this chat", "save context", "new chat", "hand off", "transfer context", "too many tokens", "start fresh", "export conversation", "context graph", "continue in new session". Also trigger proactively when the user mentions starting over in a long session.
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 "make a whiteboard animation", "draw-on explainer", "VideoScribe style", "hand-drawn explainer video", "animate a sketch being drawn", "do a doodle/scribe video", "show a hand drawing the illustration", or "animate handwriting appearing on a whiteboard". Covers SVG stroke draw-on, a marker hand that follows the path tip, staggered reveal, erase/wipe transitions, and narrated export.
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。
个性化雅思口语语料生成器。纯 Agent 内闭环（问卷 → 引导对话 → 7 步蒸馏 → 个人画像 → 静态语料网站），零后端依赖，一键安装可用。需要题库自动同步 / RAG 检索可升级到 runnable-export 模式。
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。
Interactively gather parameters for `python -m cli.inference.text_generate`, generate a concrete text generation simulation command, explain assumptions, ask for execution confirmation, then run the command and summarize performance metrics. Use when the user wants to validate a specific model, hardware profile, batch/query size, prefill or decode scenario, TP/DP/EP/MOE parallel strategy, profiling database, chrome trace, empirical metrics export, or a best row produced by throughput_optimizer.
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。
当用户希望使用 msOpProf（`msprof op` / `msprof op simulator`）对昇腾 AI 算子做上板或仿真性能调优、解释 `aic-metrics`/`trace.json`/`visualize_data.bin`、选择 device vs simulator 路径、排查 `--soc-version`/`--export`/`signal 6`/`Bad address`/热点图或流水图相关问题，或要求生成固定分析报告模板（算子基本信息 / 关键数据 TOP5 / 核心瓶颈 TOP5 / 优化建议 TOP5）时，使用本技能。它负责先判定模式、输入形态与芯片/能力边界，再给出正确命令、结果解读、固定报告输出与高频踩坑规避；不要把经验案例当成通用规则。
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。
Audit a NowStack Mobile iOS app against the App Store Review Guidelines before submission - account deletion, IAP/Restore + no Stripe on iOS, Sign in with Apple parity, permission strings, App Privacy, AI disclosure, export compliance. Use for "ns ios audit" or "will my app pass App Store review".
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。
Three-tier video pipeline: ffmpeg Quick (5s, instant) → ffmpeg Enhanced with Ken Burns (15s, polished) → Remotion Animated (60-90s, production-grade). Takes static slides from Paper MCP or any PNGs and assembles them into platform-ready video. Make sure to use this skill whenever the user has slides, images, or PNGs and wants to turn them into video — even if they just say 'make a video from these', 'animate my slides', 'I have images and need a TikTok', or 'stitch these together'. Also use when they mention ffmpeg video assembly, Remotion-animated slide assembly, Ken Burns effects, or any slides-to-video pipeline. Owns the slides→MP4 assembly pipeline; for writing, debugging, or running `remotion render` on Remotion code itself, see /remotion-best-practices; for screen-recorded product demos, see /marketing-demo. Works with any PNG source — Paper exports, Canva, screenshots, anything.
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。
Cluster keywords by search intent and map each cluster to an existing or proposed page, with cannibalization detection from Search Console. Use this skill when the user has a keyword list (saved set, brand/keyword-plan.md, GSC export, or seed topic) and needs page targets, content briefs, or a site map for SEO pages — especially before seo-content or seo-machine page generation. Triggers: "cluster keywords", "keyword mapping", "map keywords to pages", "keyword cannibalization", "which page should target".
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。
Programmatic canvas toolkit for creating, editing, and refining Excalidraw diagrams via MCP tools with real-time canvas sync. Use when an agent needs to (1) draw or lay out diagrams on a live canvas, (2) iteratively refine diagrams using describe_scene and get_canvas_screenshot to see its own work, (3) export/import .excalidraw files or PNG/SVG images, (4) save/restore canvas snapshots, (5) convert Mermaid to Excalidraw, or (6) perform element-level CRUD, alignment, distribution, grouping, duplication, and locking. Requires a running canvas server (EXPRESS_SERVER_URL, default http://127.0.0.1:3000).
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 to download paper PDFs by DOI(s). Triggers: "下载这个/这几个 DOI的 PDF/全文", "把这个 DOI 列表全部下下来", "批量下 dois.txt", "download paper(s) for DOI(s) …", "bulk-download from this Web of Science / WoS savedrecs export". Routes each DOI through publisher TDM APIs (Wiley/Elsevier/Springer) then OA fallbacks (OpenAlex/Crossref/Unpaywall), and — when --use-browser-fallback is set — a final Playwright pass that reuses institutional cookies for ACS/RSC/IEEE/AIP/IOP/APS/Science. DO NOT use for paper *search* (use Semantic Scholar / arXiv instead), Zotero import / metadata sync, or downloading *all references of* a single paper (use the ref-downloader skill).
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 `graphify-dotnet` to generate codebase knowledge graphs, architecture snapshots, and exportable repository maps from .NET or polyglot source trees, with optional AI-enriched semantic relationships.
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。
Import a memory export from another AI assistant (ChatGPT, Gemini, Claude, etc.) into this agent's memory — conversationally, additively, and with the pasted content treated as data. Use when the user wants to bring over what another assistant knows about them.
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 knowledge for migrating integrations from other platforms (Boomi, Cyclr) to Prismatic Code Native Integrations. Provides the standard integration schema, schema-to-spec mapping, confidence scoring, and migration-aware code generation patterns. Use when the user says "migrate", "convert from Boomi/Cyclr", "parse this export".
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。
Implement or update iOS SwiftUI UI from Figma designs; also use for implementation plans, token mapping, or asset export for that 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。
导出交付专家 - 将审查通过的原型导出为 HTML/PDF/PPTX 等独立运行格式
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 whenever the user wants to use AI agents to work with Penpot design files via the Penpot MCP Server. Triggers include: using Penpot through an AI agent, design files, design systems, design tokens, Penpot MCP, design-to-code, generating UI from design, auditing a design system, creating components/variants, renaming layers, exporting assets from Penpot, adding flows, interactions, animations, overlays, or prototyping in Penpot, or prompting an AI agent to read/modify a Penpot file. Also triggers when the user wants to set up Penpot MCP, connect any MCP-compatible AI agent or IDE to Penpot, or produce production-ready HTML/CSS/React from a Penpot design. Use this skill for Penpot-agent workflows — design, code, audit, prototyping, or setup.
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。