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demo-generator
Generate Onto2AI demo manifests, presentation-style review videos, and future screen-recording demo skeletons.
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。
メニュー
Generate Onto2AI demo manifests, presentation-style review videos, and future screen-recording demo skeletons.
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
Create Onto2AI product demo narration and OpenAI cedar audio files aligned to demo manifests.
Specialized skill for managing, enriching, and consolidating the Neo4j staging database.
Instructions for identifying ontology enumeration classes and rendering them in generated application models.
Rules for creating OWL ontologies strictly following the FIBO naming and documentation conventions.
Instructions for loading the Financial Industry Business Ontology (FIBO) into Neo4j.
Instructions for maintaining, running, and extending the Onto2AI MCP Server.
| name | Demo Generator |
| description | Generate Onto2AI demo manifests, presentation-style review videos, and future screen-recording demo skeletons. |
Use this skill when the user wants to create, regenerate, or standardize Onto2AI demo production files.
The current standard is the introduction demo:
cedardemo/video/review/Use demo/README4DEMO as the workflow overview and demo/introduction/README.md as the reference implementation notes.
demo/introduction/generate_introduction_video.pydemo/introduction/introduction-script.mddemo/video/introduction/introduction_demo.jsondemo/video/introduction/introduction_narration.txtdemo/audio/onto2ai_introduction_cedar.mp3demo/video/review/onto2ai_introduction_template.mp4Reuse the existing OpenAI cedar narration:
python3 demo/introduction/generate_introduction_video.py
Refresh the OpenAI cedar narration and rebuild the video:
python3 demo/introduction/generate_introduction_video.py --refresh-audio
Keep scratch frames and segment files for debugging:
python3 demo/introduction/generate_introduction_video.py --keep-work
Every generated demo should have exactly one canonical manifest at:
demo/video/<demo_name>/<demo_name>_demo.json
The manifest must carry:
narrative_lines[].text is authoritative narration content.narrative_lines[].start_ms / end_ms are authoritative timing values.slides[] or scene records define what is rendered.output_audio points to the narration artifact.output_video points to the review/final video artifact.Avoid parallel script, timing, and scene files that can drift away from the manifest. It is fine to keep a long-form source script under the relevant demo source folder, but the generator must derive the production narration from the manifest.
demo/<demo_name>/.demo/audio/.demo/video/<demo_name>/.demo/video/review/.ffprobe.1280x720, 30fps, H.264 video, AAC audio.For UI walkthroughs based on raw recordings, follow the same file contract:
demo/video/<demo_name>/<demo_name>.movdemo/video/<demo_name>/<demo_name>_demo.jsondemo/audio/<demo_name>_cedar.mp3demo/video/review/<demo_name>_synced_with_voice.mp4When creating a new screen-recording demo, build the manifest first, then derive narration audio and mux it into the recording. Do not depend on the old recording-only helper pattern; the manifest-first workflow is now the standard path.
ffmpeg and ffprobe are required for video assembly and verification.OPENAI_API_KEY and network access are required only when refreshing TTS audio.