「oop」の検索結果

Use when modeling in Autodesk Maya, such as hard-surface props, weapons, vehicles, a sci-fi crate, a game-ready or SubD film model, or a character or creature base mesh, or when asked to "clean up this model" or a scene before rigging or UVs. Also for support loops vs bevels vs creases, Smart Bevel, weighted normals, hard edges, pinching or wobbly highlights, a faceted cage, flipped faces, a triangle budget, n-gons, non-manifold geometry, mirroring a half, a low poly from a high poly, or deformation-ready topology.

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 modeling hard surface in ZBrush 2026 (sci-fi helmet, weapon, prop, armor plates, mechanical parts, kitbash, vents, panel lines, bolts, concept to game asset), when using ZModeler, Dynamic Subdivision and creasing, Live Boolean, Knife, Clip, Slice or Trim curves, IMM, ArrayMesh, NanoMesh or Panel Loops, or when edges look razor sharp, a Make Boolean Mesh fails or leaves holes, planes look wobbly, Mirror And Weld erased an edit, or ZRemesher ruins a hard-surface part.

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 task involves creating or editing a Scenario workflow graph through MCP: building an app from a brief, adding or rewiring nodes (models, prompts, approval gates, loops), authoring editor_info, publishing, unpublishing or renaming, importing an exported workflow JSON, migrating a graph built in Weavy, ComfyUI, or another node tool, copying a workflow, or turning a prompt chain into an app. Running or pricing a workflow is scenario-workflows. Keywords: node graph, editor_info, CEL.

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 dense sculpt, scan, ZBrush export or AI-generated mesh into animation-ready or game-ready topology in Maya without a mouse ("clean up this AI mesh", "retopo this character", Quad Draw, Retopologize), testing it deforms before rigging (bad elbow or wrist bend, lids popping through the eyes), or unwrapping UVs, cutting seams, setting texel density, mip-safe padding, UDIMs, lightmap UVs, stacking mirrored shells, or preparing a low poly and cage for baking. Keywords: edge flow, eye and mouth loops, Unfold3D, bake prep.

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 building or debugging Geometry Nodes, headless or live: procedural modeling, scattering objects on a surface, arrays along a curve, repeat or for-each loops, simulation zones, 5.2 physics (cloth, colliders, forces, effectors), closures, bundles, matrices, node-group assets with gizmos. Also when a GN script links nothing, shows red links, ignores modifier inputs, loses instances in a bounding box, or a simulation resets or jumps.

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 dense sculpt, scan or AI-generated mesh into clean topology in Blender, for animation, subdivision or a game low poly with a triangle budget. Also when choosing between QuadriFlow or voxel remesh and manual retopo, placing loops around eyes, mouth and joints, deciding pole placement, setting up a Shrinkwrap cage, fixing volume loss after subdivision, preparing a low poly for baking, or auditing topology for spirals, 6-poles and triangles. Keywords: retopo, retopology, quad remesh, clean up an AI mesh, edge flow, low poly, bake prep.

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 modeling hard-surface objects in Blender (sci-fi panels, props, weapons, vehicles, robots, machined or product parts) with booleans and cutters, bevel modifiers, weighted normals, or subdivision with support loops or creases. Also when shading is broken (smears on flat faces, stretching near a cut, pinching), a bevel shrinks or vanishes after a boolean, a boolean empties the mesh or leaves holes, choosing n-gons vs quads, or making a game-ready mid-poly.

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 handling audio on Scenario via MCP. Triggers include music tracks, full-length songs with vocals written from lyrics, background scores, soundtracks, game sound effects, SFX, foley, ambience, looping audio, voiceover, narration, speech, TTS, text-to-speech, dialogue, voice cloning, re-voicing a recording, scoring or adding sound to a video, transcription, or requests to create, wait on, play, or download audio files (MP3, WAV) with Scenario tools.

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 making the art for a side-scroller or 2D platformer: side-view pixel-art sprite sheets for a hero and ground enemies (run, walk, idle, attack, hurt cycles, air spin, jump and fall poses) and per-level layers (parallax background and midground, seamless wall texture, platform strip, props). Also use when a magenta key eats part of a sprite, a walk loop will not close, a slash trail keys into a solid block, generated textures do not tile, or poses on one sheet will not split.

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 transforming audio with ElevenLabs models on Scenario via MCP: text-to-speech with inline emotion tags, music from a prompt or sectioned songs, sound effects and loops, dubbing audio or video into another language, re-voicing a recording with a preset or cloned voice, or isolating speech from noise. Keywords: ElevenLabs, Eleven v3, Multilingual v2, Turbo 2.5, Music v2, Sound Effects 2, Dubbing, Voice Changer, Speech to Speech, Voice Isolator, TTS, SFX, 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 writing test fixtures for @copilotkit/aimock — mock LLM responses, tool call sequences, error injection, multi-turn agent loops, embeddings, structured output, sequential responses, or debugging fixture mismatches

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 closed and open betas that produce real signal. Beta participant selection, structured feedback collection, beta-to-GA decision criteria, and the difference between soft-launch (no structure, no signal), kitchen-sink (everyone in, no actionable feedback), and structured beta (calibrated cohort, intentional feedback loops, clear graduation criteria). Triggers on beta program, alpha test, beta cohort, beta participant, beta feedback, beta to GA decision, design partner, early access program, closed beta, open beta, RC release. Also triggers when a feature is approaching launch and the team needs structured pre-GA validation, when prior betas produced noise rather than signal, or when the team has soft-launched before but wants more structured feedback this time.

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。

Do a task end-to-end — implement, PR, CI loop, ship. ONLY invoke when the user explicitly types `/do` or `$do`; never auto-select from a natural-language request, even one that sounds like an end-to-end task.

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 an automated codex⇄Claude debate to consensus — no round cap, no deadlock exit. Two explicit subcommands. `review` (also the bare/back-compat default) — codex (reviewer) critiques the current diff and a Claude subagent (author) fixes/disputes, looping until they agree. `answer` — Claude and codex each answer a freeform prompt in parallel, then cross-check until they agree, and a unified answer is returned. Use when the user types `/codex-debate`, asks to "have codex review this", "run the codex debate", "review this PR with codex", "argue this with codex until you agree", or passes a question to "have Claude and codex debate/answer until they 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。

Iterative measurement-driven improvement loop. Measure, profile, mutate, re-measure, commit. Works for performance, bundle size, complexity, test coverage — anything quantifiable. Use when the user wants to systematically improve a metric through repeated cycles of profiling and targeted changes.

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 a skill or bring an existing one up to the same standard (validate + asm eval fix loop); run evals, tune triggering. Use when authoring, fixing, or retrofitting a skill. Don't use for invoking skills, writing prose, or Python scaffolds.

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 Codex is building or iterating on a web game (HTML/JS) and needs a reliable development + testing loop: implement small changes, run a Playwright-based test script with short input bursts and intentional pauses, inspect screenshots/text, and review console errors with render_game_to_text.

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 the code for a CopilotKit Channels agent with the Channels SDK (@copilotkit/channels) — a platform-agnostic engine that puts one AG-UI agent into Slack, Microsoft Teams, Discord, Telegram, and WhatsApp with native interactive UI. It's the engine behind OpenTag, the open-source alternative to Claude in Slack. Use this whenever the user wants to create, scaffold, or extend a Channels agent; wire an agent into Slack/Teams/Discord; add a tool, slash command, button, select, modal, or human-in-the-loop confirmation to a chat agent; or asks about createChannel, defineChannelTool, defineChannelComponent, thread.runAgent, awaitChoice, or the channels-ui JSX components. Trigger even when the user says "Slack bot", "Discord bot", or "chat agent" without naming the SDK, as long as the context is CopilotKit / Channels. The Channels API is new and easy to get wrong from memory — always ground code in this 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。

Trace bugs and manual fixes back to kits and prompts; fix at the source so the iteration loop can reproduce the fix autonomously. Six-step revision process plus the single-failure backpropagation protocol. Use when a manual hot-fix has been applied, when convergence stalls, or when the same class of bug keeps reappearing.

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 event logs, clickstreams, user paths, product funnels, retention, behavioral segments, transition graphs, step matrices, sequence patterns, and customer journeys using Retentioneering. Use when the user provides CSV, Parquet, pandas, or database event data containing user, event, and timestamp columns, or asks why users convert, churn, loop, abandon a flow, or follow particular product paths. Do not use for qualitative journey-mapping workshops or aggregate website traffic without user-level event sequences.

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 critique with 7 rated passes: Information Architecture, Interaction State Coverage, User Journey and Emotional Arc, AI Slop Risk (10-item blacklist), Design System Alignment, Responsive and Accessibility, Unresolved Decisions. Each rated 0-10 with gap-fill loop. Parallel cross-model design voices.

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。

Live-site visual QA audit with fix loop. 10-category checklist (~80 items) including AI Slop Detection (10 blacklisted patterns). Atomic commits per fix. Before/after screenshots. A-F grading. Parallel cross-model code-level design audit. Modes: Full, Quick, Deep, Diff-aware, Regression.

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 resilient, long-running, multi-step applications with AWS Lambda durable functions with automatic state persistence, retry logic, and orchestration for long-running executions. Covers the critical replay model, step operations, wait/callback patterns, error handling with saga pattern, testing with LocalDurableTestRunner. Triggers on phrases like: lambda durable functions, workflow orchestration, state machines, retry/checkpoint patterns, long-running stateful Lambda functions, saga pattern, human-in-the-loop callbacks, and reliable serverless 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。

Diagnose NCCL failures and adjacent training-pod failures on HyperPod GPU clusters (EKS or Slurm) — training hangs, AllReduce / collective-op timeouts, EFA or libfabric errors, rendezvous failures, EFA TCP fallback, /dev/shm or memlock issues, NCCL version mismatch across pods, container OOM / exit-137 / OOMKilled, GPU OOM (CUDA out of memory), CrashLoopBackOff / Pending pods, MASTER_ADDR DNS, NetworkPolicy blocking. Not for single-node hardware faults (→ hyperpod-node-debugger § G) or cluster-creation EFA / SSM failures (→ hyperpod-cluster-debugger § A / § F).

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。