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概要と使いどころ
Develop game effects from visual references and motion studies through an engine handoff, with event timing, lifecycle, readability and native review. Use for combat, status, environment or object effects.
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 implement game HUDs, menus, icons and portrait systems from visual proposals through reusable engine assets and input checks. Use when a game interface needs a coherent visual and behavior contract.
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。
Explore image concepts and make faithful edits of accepted references for 3D or creative production, with explicit model choices and visual review.
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 and review game sound banks, map chosen takes to real events, and prepare or verify runtime playback with timing, repetition and mix limits. Use for unit voices, foley, impacts, UI cues and ambience.
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。
Verify a visual game change using controlled native captures, targeted behavioral checks and a reviewable evidence record. Use for animation, VFX, HUD or scene changes whose appearance must be judged in the actual game.
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。
Integrate approved character clips into a game's movement and combat systems, including turn compensation, gait phase, event timing and interruptions. Use after animation authoring or to repair runtime transitions.
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。
Prepare a precise handoff for an agent or developer implementing a feature, continuing a task or reviewing a finished change.
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 or apply material maps and bake a textured high-poly mesh onto a game mesh, with channel, UV and export 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。
Generate and edit images, create video, audio, 3D assets or material maps through fal.ai MCP or the Python queue client. Use for fal model discovery, reference uploads, generation, recovery and local delivery.
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。
Prepare and select character motion references, or transfer approved motion to a human reference for a later mocap 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。
Turn a broad project request into a small actionable plan with concrete deliverables, dependencies and acceptance 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。
Use the official Higgsfield CLI or its Blender integration to discover models, generate requested assets and resume recorded jobs.
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。
Prepare strict-front character sheets, isolated parts and optional multiview references for 3D modeling from an approved image.
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。
Inspect a local or publicly accessible video through sampled scene frames, timestamps and a visual report, especially for motion and 3D reference 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。
Choose a workflow for 3D concepts, meshes, materials, animation, game VFX, UI, levels, audio and native visual review.
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。
Rig and animate supplied characters in Blender, revise motion from references, and deliver editable sources plus a verified game export.
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 an object or character reference image into a quality-gated, animation-ready procedural Three.js model built in code. Use for image-to-3D reconstruction, detail-accurate object rebuilds, stylized/likeness-maximized human characters, sculpt specs, and staged code generation.
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。
Track and document analytical assumptions and decisions. Use when making analytical choices, documenting trade-offs, ensuring transparency, or creating audit trails for analytical work.
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。
Explain analysis methodology to diverse audiences. Use when documenting 'how we did this' sections, building trust through transparency, or teaching analytical approaches to stakeholders.
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 self-evolution system. Collects signals from user feedback, stores execution trajectories (golden + correction pairs), analyzes patterns, proposes mutations to workspace files, and generates HTML reports. Trigger with "/evolve" or when the user asks to improve agent behavior. Also use when the user says "remember this pattern", "don't do X again", or "that was a good approach, save it".
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。
For any completed deliverable, enforce a strict multi-round subAgent review-and-revise loop via sessions_spawn. Invoke before final output or whenever high-standard quality gating is required.
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。
Investigate customer-impacting OpenAI Ruby SDK defects and privately handled security risks, then dispatch at most five evidenced, independent fixes to isolated project worktrees.
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。
Workaround for Claude Code filtering BMP PUA Unicode (U+E000-U+F8FF). Supplementary PUA Nerd Font icons like (U+F0000+, e.g. nf-md-github, nf-md-kubernetes, nf-md-battery) can be written directly. BMP PUA icons (Powerline, Font Awesome, Devicons) require placeholder syntax like {{ U+E0A0 }} or {{ nf-fa-star }} (without spaces), which hooks auto-convert. Invoke when reading or writing Starship configs, tmux themes, shell prompts, or statuslines.
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。
This skill should be used when the user asks for "deep research", "research team", "comprehensive analysis", "research report", "investigate thoroughly", "compare X vs Y in depth", or needs synthesis across multiple sources with verification. It spawns a coordinated team of researcher agents across multiple rounds, with the lead triaging findings and creating targeted follow-up tasks. Scales from Focused (2 researchers, 1-2 rounds) to Comprehensive (4 researchers, 3-4 rounds with cross-verification). Do NOT use for simple lookups, debugging, or questions answerable with 1-2 searches.
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。