DataMagic
HKUSTDial/DataMagic
DataMagic converts tabular data into narrated, animated data videos using a declarative screenplay format called DVSpec. It provides AI agents with structured guidance for data analysis, scene planning, chart selection, and voiceover timing.
Overview
DataMagic enables AI coding assistants and agents to transform structured data like CSVs or Excel spreadsheets into professional data story videos. By utilizing a renderer-agnostic specification format known as DVSpec, the skill coordinates data analysis, narrative pattern selection, chart design, and audio-synchronized animation to build multi-scene analytical videos.
Capabilities
- ▸Tabular data profiling and insight discovery
- ▸Narrative pattern matching based on data shapes
- ▸Chart type, axis, and scale selection
- ▸DVSpec declarative screenplay authoring
- ▸Voiceover scriptwriting and TTS duration synchronization
- ▸Design system token application and Remotion rendering integration
Best for
Transforming CSV or Excel tables into multi-scene narrated videos, Generating animated charts and data stories from pasted dataset snippets, Authoring and validating DVSpec screenplay plans for visualization stacks like Remotion, Refining, debugging, or expanding existing data-video generation pipelines
Works with
実タスクにどれだけ役立つか(機能の豊富さ・用途の明確さ)。 — AIによるcapabilities/use-cases解析
実装・指示の品質。 — AIによるSKILL.md/README解析
リポジトリがどれだけ活発に保守されているか。 — GitHub 最終push日時の新しさ
ドキュメントの充実度・分かりやすさ。 — README/独自要約の情報量
危険・不審な挙動が無いか。 — AIによるセキュリティレビュー
ありふれたラッパーではない独自性。 — AIによる独自性判定
コミュニティの採用度。 — GitHub Stars/Forks(対数スケール)
対応AIエージェントの広さ。 — AIによる対応エージェント判定
ライセンス不明/制限あり(Red)のSkillは総合スコアに0.85倍の補正を適用します。 ランキングはこのScoreのみで決まり、広告で変わりません。 算出方法の詳細 →
Security considerations
The skill processes local tabular data files and outputs text-based screenplay configurations. Ensure sensitive business data is handled locally and verify any external rendering scripts before execution.
Categories
Summary and analysis are original content generated by AI Skills Rank. The skill's source text is not reproduced here — view it on the linked repository.