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概要と使いどころ
Enriches inbound leads with firmographic and technographic data. Takes minimal lead info and enriches via WebSearch, Apollo, or ZoomInfo to produce a complete lead record with company size, revenue, tech stack, social profiles, and decision-maker details.
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。
Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).
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。
Decompose DAGs into execution chains using width bounds, stratification, virtual nodes, and matching. Use when minimizing workflow lanes in dependency graphs. NOT for cyclic graphs, generic scheduling, or one-off queries with no preprocessing payoff.
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。
State-of-the-art data visualization for React/Next.js/TypeScript with Tailwind CSS. Creates compelling, tested, and accessible visualizations following Tufte principles and NYT Graphics standards. Activate on "data viz", "chart", "graph", "visualization", "dashboard", "plot", "Recharts", "Nivo", "D3". NOT for static images, print graphics, or basic HTML tables.
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 build beautiful, accessible graphical interfaces — web, desktop (Electron/Tauri), and native (iOS/macOS/Android). Use for visual hierarchy and layout, color and theming (light/dark, semantic tokens, WCAG contrast), typography systems, motion and micro-interactions, accessibility, component systems and design tokens, responsive/adaptive layout, and platform-native idioms. The GUI counterpart to beautiful-cli-design. NOT for terminal/CLI output (use beautiful-cli-design) or API/data schemas.
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。
Feishuのクラウド文書を読み取り、段落の修正や追記、表の編集、新規作成を支援します。文書内の構造を確認し、画像やファイルのアップロードも扱います。
画面の余白、文字、角丸、影、動きを見直し、見た目と操作感を整えるスキル。ボタンやカードなどの細部を点検し、変更前後が分かる具体的な改善案を示します。
StripeやLinearなど54のサイトの配色・文字・余白を参考に、HTML/CSSのページを制作します。部品や画面幅に応じた表示も揃えるスキル。
Infographics: 21 layouts x 21 styles (信息图, 可视化).
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。
Swiss-inspired creative-mode presentation template skill with bold editorial typography, high-contrast geometric cards, interactive slide navigation, theme switching, hotspot overlays, and palette choreography in a single-file HTML artifact. Use when users ask for a premium presentation-style landing, a Swiss/brutalist deck look, or a creative launch page with rich interactions.
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 business domain knowledge from a codebase and generate an interactive domain flow graph. Works standalone (lightweight scan) or derives from an existing /understand knowledge graph.
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。
Automate Contentful Graphql tasks via Rube MCP (Composio). Always search tools first for current schemas.
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 code by graph community detection via npx ruvector@0.2.25 hooks graph-cluster (spectral / Louvain)
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。
Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel
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 you are about to create ANY chart, graph, plot, dashboard, or data visualization, in ANY output medium — an HTML or React artifact, inline SVG, plotting code in any library (matplotlib, plotly, d3, Recharts, …), an image/PNG you will render and upload, or a chart shared into Slack. Read it BEFORE writing the first line of chart code, choosing chart colors, building a stat tile / meter / KPI row, or laying out a dashboard. When the destination is a first-party document connector (host-designated, never self-described) that renders live charts, hand it the rows (inline, or as an uploaded data file the chart cites) rather than a rendered PNG/SVG — a picture of a chart loses hover, data inspection and per-value comments. Produces visualizations that read as one system — elegant, accessible, consistent in light and dark — using a brand-neutral placeholder palette you swap for your own. Teaches a design-system-agnostic method: a form heuristic, a color formula with a runnable validator, mark specs, and interaction rules. A validated default palette is documented in `references/palette.md` — swap that file's values for your brand's. Triggers on: "chart", "graph", "plot", "data viz", "visualization", "dashboard", "analytics", "visualize data", "categorical colors", "sequential / diverging palette", "stat tile", "sparkline", "heatmap", "legend", "axis", "tooltip", "chart colors", "color by series".
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。
Security-test a REST, GraphQL, or gRPC API with Strix — autonomous agents that enumerate endpoints from an OpenAPI/GraphQL schema (or by crawling), then actually exploit the API-specific vulnerability classes in the OWASP API Security Top 10 (2023) — broken object-level authorization (BOLA/IDOR), broken object property level authorization (excessive data exposure and mass assignment), broken function-level authorization, unrestricted resource consumption, SSRF, injection, and auth/token flaws. Every finding comes with a working proof-of-concept request. Use when the user asks to pentest, security-test, audit, or find vulnerabilities in an API, endpoint, or backend service.
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 general website/URL and turn it into a HyperFrames video (site tour, showcase, or social clip from the site's own visuals). Uses headless Chrome screenshots + brand assets. Use when intent is general — portfolio/blog/landing-page showcase or social clip from the site. NOT for: product/SaaS launch or promo (→ /product-launch-video, even from a URL); topic explainer with no site (→ /faceless-explainer); GitHub PR (→ /pr-to-video); adding captions to existing video (→ /embedded-captions); short unnarrated page-highlight motion graphic (→ /motion-graphics). Unclear launch-vs-general-site? Ask one question or start at /hyperframes.
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。
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
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。
Turn arbitrary text — an article, notes, a topic, a brief — into a faceless explainer video: there is no site or footage to capture, so the visuals are invented per scene (typography, abstract graphics, diagrams, data-viz). Use for topic explainers, concept breakdowns, how-tos, listicles. Not a video built from a website (/product-launch-video — promo or tour). Unclear → /hyperframes.
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。
Derive new Office files from structural selections without touching the original. Use when the user points at part of a spreadsheet, Word document, PDF, or PowerPoint deck (a worksheet range, paragraph, page, slide, shape, or a pasted selection-ref block) and wants it extracted, converted, or edited — the result is always a NEW file; the source file is never modified. Covers xlsx range extraction to csv/markdown/xlsx, docx paragraph extraction and text replacement, pdf page extraction, pptx slide/shape/table-cell extraction and editing, and targeted xlsx cell edits.
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。
Windows-first CLI harness for Nsight Graphics capture, GPU Trace summary, and ngfx-replay 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。
Builds and troubleshoots TorchDrug 0.2.1 workflows for molecular graphs, property prediction, self-supervised pretraining, molecule generation, retrosynthesis, protein representation learning, and knowledge graph reasoning. Use when code imports torchdrug or needs its datasets, models, tasks, or Engine.
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。
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS, cuCIM, KvikIO, Warp, Newton, Numba-CUDA, or RAFT questions; and profiling, memory-transfer, kernel, or multi-GPU bottlenecks. Also use when large data-parallel Python code is slow and GPU acceleration is a plausible option, even if the user does not name CUDA.
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。
Queries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationships. Use for Biolink-constrained RTX-KG2 lookup, explicit selected-provider ARAX federation, separate entity normalization, qualifier-aware graph traversal, and inspection of TRAPI edge bindings, publications, and knowledge-source provenance. Do not use for inference, ranking, open-ended pathfinding, clinical guidance, or sensitive queries.
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。