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概要と使いどころ
Build, inspect, audit, and refactor Blender Geometry Nodes systems for procedural models, instancing, modular effects, curves, scattering, flocks, data visualization, fields, simulation zones, and node-graph cleanup. Use whenever a Blender task specifically calls for Geometry Nodes, reusable procedural node graphs, node connections/layout, or a scalable procedural asset.
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 detailed feature specifications with functional requirements, edge cases, data models, API contracts, and UX flows. Create comprehensive technical specifications that enable clear implementation.
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。
Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.
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。
Complete, populate and fill out 3-statement financial model templates (Income Statement, Balance Sheet, Cash Flow Statement) . Use when asked to fill out model templates, complete existing model frameworks, populate financial models with data, complete a partially filled IS/BS/CF framework, or link integrated financial statements within an existing template structure. Triggers include requests to fill in, complete, or populate a 3-statement model template
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 institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format. **Perfect for:** - Public company valuation (M&A, investment analysis) - Benchmarking performance vs. industry peers - Pricing IPOs or funding rounds - Identifying valuation outliers (over/under-valued) - Supporting investment committee presentations - Creating sector overview reports **Not ideal for:** - Private companies without comparable public peers - Highly diversified conglomerates - Distressed/bankrupt companies - Pre-revenue startups - Companies with unique business models
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 institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.
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。
UE (user experience engineering) skill for defining end-to-end user experience behavior and interaction logic. Use for tasks like flow design, interaction models, state machines, error recovery, input validation, usability heuristics, accessibility, and turning UX intent into testable acceptance criteria for implementation.
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。
generate, refine, validate, and render diagrams from natural language, notes, code snippets, schemas, tables, or existing diagram source. use for flowcharts, swimlanes, sequence diagrams, state diagrams, er diagrams, class diagrams, architecture/c4-style diagrams, dependency graphs, gantt charts, mind maps, user journeys, sankey-style flows, org charts, network graphs, and other visual models. supports mermaid by default, graphviz dot for complex graph layout, plantuml for uml-heavy engineering diagrams, and svg output when direct markup is more reliable.
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。
Connects Claude Code, Codex, Cursor, and other MCP hosts to Writingmate for model discovery, text comparison, image generation, and video generation with Seedance, Sora, Veo, Kling, PixVerse, and other available models.
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 for writing, reviewing, debugging, or testing Pandera schemas and runtime validation for Polars DataFrame or LazyFrame pipelines installed with pandera[polars]. Trigger on pandera.polars DataFrameSchema, DataFrameModel, Column, Field, Check, PolarsData, decorators, coercion, strictness, lazy error collection, and validation-depth decisions. Do not use for pandas-backed Pandera, Pydantic object models, Polars transformations without Pandera, static dataframe typing alone, or generic data-quality platforms.
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。
Kaggle-first end-to-end competition workflow for scored submissions. Use when Codex must run Kaggle or competitive ML workflows through scored submission, including code competitions, validation, metrics, policy-safe public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling/stacking, proactive multi-notebook architectures, producer notebooks that train models and export private Kaggle artifact datasets, downstream consumer notebooks, Kaggle GPU offload, kagglehub access, hidden-test debugging, and public score retrieval.
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。
Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.
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。
Redpanda's Agentic Data Plane: governance infrastructure for building, running, and governing AI agents and MCP servers, plus a proxying AI Gateway for LLM providers, operated via `rpk ai` and the ADP API. Use when creating or managing AI agents (managed or self-managed) via `rpk ai agent` or `AgentRegistryService`; configuring MCP servers (remote or managed catalog, code mode, auth); setting up LLM providers or querying models via `rpk ai llm`/`rpk ai model` or the AI Gateway proxy; or configuring budgets, guardrails, or Cedar access-control policies through the governance APIs. Also covers reading agent transcripts and spending insights, and wiring OAuth clients or providers to the aigw Authorization Server. For the separate rpk cloud mcp control-plane MCP server, see `/redpanda:rpk-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。
Trigger this skill when building applications with Gemma or for general knowledge inquiries related to Gemma models (e.g. prompt structure, capabilities). Covers model selection, development workflows, and deployment best practices.
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 only memory skill that watches on its own. No database. No vectors. No manual saves. Just an LLM observer that compresses your conversations into prioritised notes, consolidates when they grow, and recovers anything missed. Five layers of redundancy, zero maintenance. ~$0.00/month (using free-tier models). While other memory skills ask you to remember to remember, this one just pays attention.
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。
Trigger this skill when the user wants to train, fine-tune, or adapt Gemma models (e.g. SFT, DPO, RLHF, Reward Modeling) on local hardware. Covers TRL, Unsloth, dataset preparation, validation, and GGUF/LiteRT conversion.
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。
Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Keeps search noise on disk, hands the agent one path or block. Use for any audio, image, icon, logo, voiceover, caption, color-grading, or media-asset need.
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 persistent coding sessions across Claude Code, Codex, Antigravity (agy), Cursor, and OpenCode engines. Use when orchestrating multi-engine coding agents, starting/sending/stopping sessions, running multi-agent council collaborations, cross-session messaging, ultraplan deep planning, ultrareview parallel code review, autoloop autonomous workspace iteration, ultraapp building deployable web apps from a structured Q&A interview, switching models/tools at runtime, exposing the orchestrator's 69 tools as an MCP server to Hermes Agent / Claude Desktop / Cursor / Cline / Continue / Zed / Windsurf / Goose, or running as an Agent Client Protocol (ACP) agent that Zed / JetBrains / Neovim / Emacs / VS Code / dsh can drive directly. Triggers on "start a session", "send to session", "run council", "ultraplan", "ultrareview", "autoloop", "ultraapp", "Forge tab", "build a web app", "one-click app", "AppSpec", "autonomous iteration", "iterate until goal", "deep paper review", "auto research", "switch model", "multi-agent", "coding session", "session inbox", "cursor agent", "opencode", "mcp server", "clawo-mcp", "hermes mcp", "model context protocol", "ultracode", "dynamic workflow", "fanout", "fan-out", "best-of-N", "steer turn", "interrupt turn", "fork thread", "rollback turns", "acp", "agent client protocol", "clawo acp", "zed agent", "jetbrains agent", "external agent", "dsh subagent", "deepseek harness".
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。
Acts as a director and previs supervisor for film, video, and AI filmmaking. Turns scripts, prose, briefs, or existing image and video assets into production deliverables — subtext breakdown, beat sheet, director's book, blocking and staging, shot list with coverage, keyframe and storyboard prompts, image-to-video motion prompts, sound and dialogue plans, edit timelines, continuity bibles, and QC repair notes. Carries genre playbooks, a controlled prompt lexicon, a coded failure-diagnosis manual, and capability-first adapters for current video and image models. Optionally applies one named director's style lens — Spielberg, Hitchcock, Kubrick, Kurosawa, Scorsese, Fellini, Bergman, Tarkovsky, Wong Kar-wai, Nolan, Villeneuve, Fincher, Refn, Bi Gan, Zhang Yimou, Hou Hsiao-hsien, Park Chan-wook, Malick, Michael Mann, Coen Brothers. Use for shot planning, blocking, staging, camera movement, visual continuity, storyboard and keyframe design, prompt repair, "in the style of X" direction, and any AI video workflow.
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 choosing between engines or models for an agent pipeline and the answer must come from measurement on your own data, not from marketing pages: speech recognition for meeting recordings, the model that turns a transcript into notes, the critic model that checks it. Runs every variant in an isolated container, measures time, cost per hour of input (USD and RUB, with price source and date) and quality (WER/CER and course terms for ASR; code checks plus a judge of a different model for LLM steps), writes results.json/csv and one static analytics page. Triggers on "бенчмарк", "сравни движки", "сколько стоит час записи", "какую модель взять для пайплайна", "benchmark the pipeline", "compare ASR engines".
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.js 3D graphics library - scene setup, geometry, materials, lighting, textures, animation, loaders, shaders, postprocessing, interaction. Use when building 3D web experiences, creating WebGL visualizations, working with GLTF models, implementing custom shaders, or adding interactive 3D elements to web applications.
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。
Deploy ML models with FastAPI, Docker, Kubernetes. Use for serving predictions, containerization, monitoring, drift detection, or encountering latency issues, health check failures, version conflicts.
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。
Train ML models with scikit-learn, PyTorch, TensorFlow. Use for classification/regression, neural networks, hyperparameter tuning, or encountering overfitting, underfitting, convergence 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。
End-to-end 3D printing for Bambu Lab printers. Finds models online (MakerWorld, Printables), generates them with AI (text-to-3D, image-to-3D) or as exact-dimension parametric CAD, checks and repairs printability, converts textures to AMS multi-color, renders previews, opens them in Bambu Studio for the user to print, and reads printer status, AMS filaments and print progress. Use this whenever the user wants to 3D print something, design or model an object for printing, work with STL/3MF/OBJ/GLB files for a printer, check on a Bambu Lab printer (A1, A1 Mini, A2L, P1S, P2S, X1C, X1E, X2D, H2C, H2S, H2D, H2D Pro), or asks about AMS filament, slicing or print progress, even if they don't say "Bambu".
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。