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Use when creating, planning, auditing, or choosing tools for neural-network architecture figures, CNN diagrams, AI model schematic diagrams, NN-SVG, PlotNeuralNet, draw_convnet, LaTeX/TikZ neural-network figures, or publication-ready model architecture visuals.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Design and review active learning implementation support for university teachers, including classroom activity structures, preparation workflow, student participation, assessment alignment, and AI-agent support points.
Turn dissertation evidence into an AI agent design specification for supporting active learning implementation, including user scenarios, functions, interaction flow, boundaries, failure modes, and design rationale.
Synthesize confirmed co-design, design-elicitation, prototype-feedback, or participant-generated design outputs into requirements, design principles, prototype changes, participant contribution maps, and design decision logs.
Design specifications for dissertation figures such as conceptual frameworks, concept-card/interview process diagrams, AI-agent workflow diagrams, adoption-condition models, and findings maps.
Maintain a lightweight dissertation research wiki with project memory, literature notes, methodology decisions, supervisor feedback, design rationale, and open questions.
Audit an AI agent prototype or design concept for usability, pedagogical fit, teacher feedback, active learning support, evidence quality, and next design iterations.
| name | research-neural-network-figure |
| description | Use when creating, planning, auditing, or choosing tools for neural-network architecture figures, CNN diagrams, AI model schematic diagrams, NN-SVG, PlotNeuralNet, draw_convnet, LaTeX/TikZ neural-network figures, or publication-ready model architecture visuals. |
Use this skill to choose and govern neural-network architecture figure workflows. It is a tool-selection and figure-quality skill, not a source of evidence.
Before selecting a tool, identify:
For formal research outputs, pair this skill with source-first, privacy/compliance, figure-quality, and document-quality gates.
| Tool | Use When | Boundary |
|---|---|---|
| NN-SVG | quick editable SVG neural-network sketches; architecture is simple enough for manual configuration | Online tool; do not upload private or sensitive data; user may need to export manually |
| PlotNeuralNet | paper-grade LaTeX/TikZ architecture diagrams; reproducible figure code is useful | Do not run external repo scripts unless the user asks; check local LaTeX availability first |
| draw_convnet | lightweight convolutional-network figure only | Check licence before copying or redistributing code |
| Custom Mermaid / TikZ / Python / SVG | the figure is conceptual, non-standard, or external tools do not fit | Keep diagram source and export path auditable |
