データ・AIのスキル

Use when structuring Unity 6.3 C# code: ScriptableObject data vs runtime state, events and services, inventory, health, save and load, Input System actions and key rebinding, async with Awaitable, assembly definitions, Enter Play Mode and domain reload, .meta files, Git, Smart Merge and LFS. Also when 'my save works in the Editor but not in the build', statics keep values on the second Play, events fire twice or never, an await runs after its object died, rebinds are lost on relaunch, a renamed class loses its data, a scene merge breaks.

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 UE5 task involves Niagara or Chaos destruction: a Niagara fireball, projectile trail, impact explosion, muzzle flash, spell, smoke, sparks, debris, Niagara fluids or flipbooks; "Niagara is too expensive", stat NiagaraOverview, Effect Types, pooling, Data Channels, lightweight emitters, VFX scalability; judging an effect's readability, value, color, timing, white blowout or strobing; or a wall that shatters, geometry collection fracture, Dataflow, damage thresholds, floating chunks, debris cost, Chaos Visual Debugger.

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 or fixing real-time VFX in Unity 6.3: explosions, fireballs, projectiles with muzzle, trail and impact, spells, slashes, shockwaves, smoke, sparks, Particle System (Shuriken) or VFX Graph ('VFX Graph explosion', 'particles look bad', 'effect kills fps on mobile', 'too much overdraw'), mesh effects with scrolling textures, an uber VFX shader with LUT ramps, Custom Data and custom vertex streams, flipbooks and VFX textures, pink particles after URP upgrade, VFX budgets and readability.

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 UE5 task involves characters in motion: "import FBX from Maya" with a skeleton, "retarget animations", IK Rig, IK Retargeter, feet sinking or floating after retarget, mocap cleanup, Motion Matching, Pose Search, Choosers, GASP, state machine vs motion matching, root motion, offset root bone, foot IK, Control Rig, Animation Blueprint cost, "animation is expensive", budget allocator, URO, MetaHuman LODs, ML Deformer, cloth.

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 animating 2D game art with Scenario: walk, idle or attack cycles in 4 or 8 directions, isometric sprite sheets, animated GIFs, frame-by-frame pixel art animation, VFX loops such as fire or smoke, looping a sprite seamlessly, animating an existing character image, a full animation sheet from one prompt, extracting animation frames from a generated video, or slicing a sprite sheet into engine-ready frames for Unity, Godot, or Unreal. Keywords: spritesheet, keyframes, frame grid, GIF.

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 extending video with Google Veo models on Scenario via MCP: text-to-video, image-to-video from a first frame, first and last frame transitions, reference-to-video (R2V) with asset or style reference images, native audio with dialogue, sound effects, and ambience, negative prompts, seeded reruns, extending a 16:9 clip, or choosing a quality, fast, or lite tier. Keywords: Veo 3.1, Veo 3.1 Fast, Veo 3.1 Lite, Extend Video, Google, T2V, I2V, V2V, 720p, 1080p.

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 connecting an AI agent to Scenario (scenario.com) through MCP, or when a task involves generating images, video, 3D, audio, sprites, textures, or game assets. Also when picking a Scenario model, running a LoRA, refining a generation prompt, uploading reference images, waiting on generation jobs, checking credits or quota, hitting Scenario auth, scope, or Forbidden errors, or setting up mcp.scenario.com in Claude Code, Cursor, VSCode, or another agent.

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 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。

Use when generating, extending, or editing video with Gemini Omni models on Scenario via MCP: text-to-video, image-to-video from a first frame, reference-to-video keeping a character, product, or place consistent, appending footage to a clip, restyling footage by prompt (season, wardrobe, art style), native audio with dialogue and ambience, or picking between first-frame and reference conditioning. Keywords: Gemini Omni Flash, 1.1 Flash, Google, T2V, I2V, V2V, extend, subject consistency.

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 music with MiniMax models on Scenario via MCP: full songs with vocals from a lyric sheet, structure tags like [Verse] and [Chorus], auto-written lyrics from a plain-language brief, instrumental tracks from a style prompt, or covering an uploaded MP3 or WAV in a new genre while keeping the melody. Keywords: MiniMax Music 3.0, Music Cover, Hailuo, text-to-music, audio-to-audio, song generation, lyrics, vocals, instrumental, BPM, genre swap.

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 Scenario user wants to report a bug or request a change, on the public tracker at github.com/scenario-labs/skills or by email to support@scenario.com: turning a failed generation, MCP tool error, or unclear skill into a reproducible report, collecting trace ids with diagnostics_run, stripping keys, signed asset URLs, and personal data, asking before sharing a team or project id, or building a prefilled issue URL. Keywords: file an issue, feature request, feedback.

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 answering Scenario admin analytics questions about Creative Unit consumption, most-used models, usage by user or project, AI adoption observability, cached usage data, CSV exports, enterprise PDF reports with charts, or a local analytics dashboard. Keywords: usage API, CU, analytics, adoption, reporting, consumption, cache.

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 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 handling 3D assets through the Scenario MCP server, including text-to-3D or image-to-3D meshes, GPT-6 Astra 3D or Claude Opus 5.5 3D, GLB, FBX, OBJ, STL, or VOX files, PBR-textured or game-ready models, voxel models, multi-view reconstruction, editing a mesh by prompt, retexture, remesh, UV unwrap, auto-rigging a biped or quadruped, or retargeting an animation, previewing a mesh in the 3D viewer, or downloading a model for import into Unity, Unreal, Godot, or Blender.

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 Reve models on Scenario via MCP: text-to-image from a prompt alone, instruction edits (swap poster text, recolor a product, change materials, relight or restyle a scene), merging references with consistent subjects, blending up to 6 images into one composite, or choosing between Reve v2.1 and Reve Remix. Keywords: Reve v2.1, Reve Remix, Reve AI, txt2img, img2img, frame tags, compositing, style blending, text swap.

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 Runway models on Scenario via MCP: text-to-video or image-to-video from a first frame with Gen4.5 (cinematic motion, sequenced actions, camera choreography), or video-to-video editing of real footage with Aleph 2 (remove objects, swap products, restyle or relight shots, keyframe-pinned reference images, motion and audio preserved). Keywords: Runway ML, Gen4.5, Gen-4.5, Aleph, T2V, I2V, V2V, first frame.

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 Scenario generation is blocked, refused, or returns a moderation or sensitive-content error, when a video is rejected after rendering or its audio track is flagged, when an output is flagged for likeness to a real person or for IP and copyright detection, when the same prompt passes on one model and fails on another, or when a team's own characters, weapons, or props get flagged. Keywords: blocked prompt, content moderation, refused generation, provider filter, false positive.

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 creating or refining 3D assets with Meshy models on Scenario via MCP: image-to-3D from one photo or 1-4 multi-view angles, text-to-3D, retexturing an existing GLB, remeshing to a target polycount, UV unwrapping, auto-rigging a humanoid character, or applying a library animation clip. Keywords: Meshy 7 and Meshy 6, Ultra mode, Smart Topology, PBR maps, texture prompt, triangle or quad topology, game-ready mesh, A-pose, T-pose, GLB pipeline.

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 generated assets must keep a consistent style, character, or product look and references stop scaling, or when a user asks to train a custom model through the Scenario MCP, fine-tune a LoRA, clone a voice, curate a training dataset, choose a base model, set epochs and sample prompts, estimate training cost, diagnose a trained model that lost its identity or has one epoch, or generate with a trained model. Keywords: custom model, LoRA, dataset curation, epoch previews.

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 3D assets with Rodin Hyper3D models on Scenario via MCP: image-to-3D from up to five multiview stills, text-to-3D from a prompt, fast prototyping versus full quality tiers, quad or triangle topology, PBR materials, HighPack 4K textures, T-pose or A-pose characters for rigging, or splitting a finished mesh into parts and retexturing it with Bang!. Keywords: Rodin Gen-2.5, Hyper3D, Deemos, image to 3D, text to 3D, part segmentation, texture delight.

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。

Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and randomize them, then judge and merge into one final plan. Use when you need a robust, bias-resistant planning workflow, structured JSON outputs, retries, and failure handling across multiple CLI agents.

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, transform, audit, and migrate prompts for GPT-5.6 Sol using outcome-first contracts, explicit success criteria, evidence and tool rules, approval boundaries, output requirements, and stop conditions. Use when someone asks for a GPT-5.6 prompt, wants an existing prompt optimized for GPT-5.6, or needs a prompt stack adapted from an older 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。