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Use when generating or editing video on Scenario via MCP: text-to-video, a music video from a song, image-to-video (still animation, frame anchors), motion prompting, lipsync and talking avatars, dubbing a clip, video upscale to 4K, prompt-based editing, trim, split, concat, extend, reframe, resize, background removal, frame or audio extraction, long video jobs, or a clip over a duration limit. Keywords: txt2video, img2video, video2video, audio2video, I2V, T2V, V2V, localization.

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 drawing or animating with Grease Pencil in Blender 5.x from Python: 2D or 2.5D illustration, frame-by-frame animation, a cutout or part-based 2D character, strokes with pressure, filled shapes with holes, in-betweens and interpolation, onion skin, Line Art outlines, strokes on 3D meshes, NPR or hybrid motion graphics. Also when GP code fails (GPENCIL, frame.strokes, grease_pencil_modifiers), fills do not show, colors render dark, or draw brushes will not run from a script.

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 generating or editing video with Wan models on Scenario via MCP: text-to-video, image-to-video from a still, first and last frame brackets, extending a clip, instruction-based video editing, character motion transfer or person replacement (Animate), aspect ratio reframing, video outpainting, uploaded-audio sync or auto-generated audio, or multi-shot prompts with timing brackets. Keywords: Wan 2.7, 2.6, 2.5, 2.2, Alibaba, VACE, T2V, I2V, V2V, lip-sync, multiShots.

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 generating or editing video with Seedance models on Scenario via MCP: text-to-video, image-to-video, first and last frame anchors, reference-to-video from identity, product, or world references, prompt-based editing, extending a clip, audio-conditioned motion or voice, shot sound without music, first-frame versus reference conditioning, or an output blocked by moderation. Keywords: Seedance 2.5 and 2.0, ByteDance, T2V, I2V, V2V, native audio, OutputVideoSensitiveContentDetected.

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 generating or editing images with Luma Uni-1 models on Scenario via MCP: text-to-image, prompt-based editing of an existing image, style or character reference images with named roles, web search grounding for real-world subjects, rendering exact title text into posters, aspect ratio control, or choosing between Uni-1 Max and Uni-1. Keywords: Luma Labs, Uni-1, Photon, txt2img, img2img, image edit, reference images, webSearch, reasoning image model.

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 generating or editing video with Grok Imagine models on Scenario via MCP: text-to-video, image-to-video from a first frame, reference-to-video with @image tags for consistent people, products, or clothing, prompt-based editing, extending a clip from its last frame, native audio with lip-synced dialogue and sound effects, or choosing between first-frame and reference conditioning. Keywords: Grok Imagine Video 1.5, R2V, Grok Edit Video, Grok Extend Video, xAI, T2V, I2V, V2V.

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 generating or editing images with Microsoft MAI Image models on Scenario via MCP: photoreal or stylized text-to-image with legible in-image typography, posters, packaging, magazine covers, ads, key art, or instruction-based editing such as text swaps, recoloring, object removal or replacement, background swaps, lighting changes, and full restyles. Keywords: MAI Image 2.5, 2.5 Pro, 2.5 Edit, 2.5 Pro Edit, Microsoft, txt2img, img2img, typography, text rendering, image edit.

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 generating or editing video with Kling models on Scenario via MCP: text-to-video, image-to-video with first and last frames, multi-shot sequences with per-shot prompts, consistent characters via elements and reference images, prompt-based video editing, motion transfer from a driving video (motion control, mocap), lipsync to audio or text, talking avatars, native audio and dialogue, or picking 720p, 1080p, or 4K tiers. Keywords: Kling V3, O1, 2.6, Omni, Kuaishou, T2V, I2V, V2V.

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。

A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.

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。

Runs a guided, end-to-end security review of a Power Pages site and consolidates every finding into one HTML report covering source code and dependencies, the live site, browser headers, firewall, authentication, and role-based permissions. Use when the user wants a full security review, a release-readiness check before publishing, a code-and-config check during development, live site monitoring, or asks open-ended questions like "review my site security", "is my site safe to ship", "do a security check", "monitor my site" — even if they do not name the individual checks.

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。

Creates Dataverse tables, columns, and relationships for a Power Pages site based on a data model proposal. Use when the user wants to set up the data model, create database tables, or build the Dataverse schema for their site.

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。

Tests a deployed, activated Power Pages site at runtime using browser-based navigation, page crawling, and API request verification via Playwright. Use when the user wants to test, verify, or smoke-test their deployed site.

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。

Integrates Power Automate cloud flows into a Power Pages site. Lists available flows, suggests relevant ones based on intent, identifies scenarios and web roles, creates metadata files, and generates client-side code to call flows. Handles both new flow registration and adding already-registered flows to additional pages without re-creating metadata. Use when the user wants to add, connect, register, or link a Power Automate cloud flow to their site.

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 3D CGI and rendered video prompts for Seedance 2.0 on Higgsfield. Use whenever the user wants 3D rendered, CGI, Pixar-style, Unreal Engine, photorealistic 3D, computer-generated, or digitally rendered video content. Triggers on: 3D animation, CGI, rendered, Blender, Unreal Engine, octane render, ray tracing, volumetric, subsurface scattering, physically based rendering, or any 3D/CG video request. Always use even if the user just says "make it look 3D" or describes a rendered aesthetic.

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。

Produce honest product reviews and buying guides without fabricated first-hand experience, using disclosed evidence tiers: verified specs, owner-experience synthesis at scale, expert triangulation, and hands-on only when true. Use this skill whenever the user wants to write product reviews or buying guides without hands-on access, set up a review methodology, add evidence disclosure to review content, align reviews with Google's reviews system or FTC affiliate disclosure expectations, or decide when Review and Product schema are honest to use. Triggers on product review, buying guide, best-of list, review methodology, evidence basis, hands-on testing, we tested, affiliate review site, review disclosure, methodology block, original research, reviews system. Also triggers when review content claims testing that did not happen, or when an affiliate site needs a trust mechanism that survives scrutiny.

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。

How to read paid media dashboards without fooling yourself. Attribution models, platform reporting quirks, multi-platform reconciliation, ROAS vs LTV horizon traps, statistical noise in performance metrics, incrementality testing, and the failure modes that produce expensive lessons. Triggers on read paid media dashboard, attribution analysis, ROAS vs LTV, multi-platform reconciliation, ad incrementality, geo holdout, conversion lift study, ghost bidding, paid media reporting, board-deck paid media metrics, blended CAC, MMM, MTA, last-click attribution. Also triggers when a marketer is about to scale, kill, or rebudget a campaign based on platform metrics, or when reconciling platform reports against warehouse revenue.

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。

Running experiments out of the data warehouse instead of via dedicated experiment platforms. SQL-based assignment, exposure logging discipline, metric definitions in dbt models, statistical analysis in SQL or Python, variance reduction with CUPED, sequential testing, and the operational tradeoffs vs platforms like Statsig and Optimizely. Triggers on warehouse-native experimentation, run experiments in BigQuery, run experiments in Snowflake, dbt experiments, SQL t-test, CUPED variance reduction, exposure log, sample ratio mismatch, sequential testing, mSPRT, doubly robust estimation, build vs buy experimentation. Also triggers when the team is choosing between platform and warehouse, building warehouse-native experiment infrastructure, auditing one, or running an experiment with a custom metric the platform cannot handle.

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 when adding Nix-based local runs for an existing Playwright e2e suite. Provides a self-contained `tests/shell.nix` that uses `nixpkgs-latest` for `playwright-driver.browsers`, plus a justfile entry — works on NixOS where `npx playwright install --with-deps` cannot.

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。

Run a structural-review debate between two lenses — lowy (volatility-based decomposition) and hickey (structural simplicity) — on the current diff. Each reviews independently, then they cross-examine every finding until they agree per-finding, and the agreed fixes are applied. Use when the user types `/lens-debate`, or asks to "have lowy and hickey review this", "run the lens debate", "debate this diff structurally", or "argue the structure of this PR until the lenses agree".

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。

Evaluate architecture and module boundaries for volatility-based decomposition using Juval Lowy's framework (from "Righting Software", building on Parnas 1972). Use when reviewing module splits, service boundaries, new abstractions, or any decomposition decision. Trigger on phrases like "where should this boundary be", "how to split this", "module boundaries", "encapsulate change", "volatility", or references to Lowy, Parnas, or "Righting Software". Complements /hickey (interleaved concerns) with a different lens (change encapsulation).

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。

Conventions for writing justfile recipes in Nix-based 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。

Expert third-party risk management (TPRM) advisor — a vendor risk analyst for the full lifecycle: risk-based vendor tiering, tailored due-diligence questionnaires (SIG-style or mapped to ISO 27001, SOC 2, DORA, NIS2, HIPAA), SOC 2 Type II report review (exceptions, carve-outs, CUECs, bridge letters), DPA and sub-processor review under GDPR Art. 28, contract security addenda (DORA Art. 30 provisions), ongoing monitoring programmes, and vendor offboarding. Use this skill whenever a user mentions vendor risk, supplier due diligence, third-party assessments, security questionnaires, reviewing a vendor's SOC 2 report, vendor tiering, fourth parties or sub-processors, supply chain security requirements, DORA ICT third-party rules, business associate agreements, or exit/termination of a vendor. Also trigger for 'a customer sent us a questionnaire' and 'how do I assess this vendor' style requests.

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。

Cilium and Hubble network observability for Kubernetes. Use when managing network policies, observing traffic flows, or troubleshooting connectivity with eBPF-based networking.

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。

WeChat Official Account topic planning and content calendar management. Based on WeChat article search and trending analysis, generates differentiated topic recommendations and outputs structured content calendars. Activated when users mention "topic", "planning", "content calendar", "trending", or "what to write next week".

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。