Conference Paper Video

SkillMedia

Lets your agent turn an academic paper into a narrated conference video with scenes, captions, and an MP4.

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Conference Paper Video skill

About this skill

The open-source design agent and harness, better than Claude Design on academic communication artifacts production. This DesignHarness can also be used with any coding harness you like ( Codex/Claude Code/Kimi Code/Pi/OpenCode etc..) and any agentic model you want.

What this skill tells your AI

The instructions your AI receives, as published by yaxin9luo/autodesign in skills/video/conference_video/SKILL.md and read by ahel’s review.

Use for a narrated conference video derived from an academic paper. The source is an editable HyperFrames HTML timeline; the MP4 is a validated delivery, not the authoring source.

Stage: enhance

Expand the paper into a 10-14 scene English narrative lasting 300-600 seconds. Choose the target duration from the paper's complexity, evidence density, and explanation needs; preserve an already-selected target during repair or resume. Preserve the paper's claims, terminology, figures, tables, and provenance.

Stage: plan

Create ordered html_artifact scene frames with explicit durations and English speaker_notes. Use 1920x1080 at 30 fps. Select male or female; the runtime records the corresponding deterministic Kokoro voice id. Read delivery_contract before authoring. Write local-only HyperFrames HTML with native text and local source figures. Use exactly one data-composition-id root; static scenes must set data-no-timeline, while animated work must register a seekable window.__timelines entry. Every timed scene and narration audio element must have literal class="clip"; data-hf-clip alone is invalid. Do not use requestAnimationFrame, remote scripts, styles, fonts, images, media, iframes, data URLs, or network APIs. Keep all animation deterministic and seekable.

Keep all 10-14 scene sections directly in project/index.html; do not move them into data-composition-src files to address file-size or track-density warnings. Those lint warnings are advisory, while the ordered root scenes are part of the strict delivery contract. Use renderer-supported system fonts, or provide a local @font-face source for every custom font.

Stage: critique

Reject placeholders, external assets, missing narration, fewer than 10 or more than 14 scenes, timelines outside 300-600 seconds, lint errors, render errors, stale MP4 files, and incomplete media probes.

Stage: repair

Repair every blocking contract failure without restructuring valid root scenes in response to advisory lint warnings. Then require index.html, English transcript, English SRT and VTT, Kokoro voice metadata, a fresh MP4, ffprobe evidence, and delivery_manifest.json. Whisper may compare rendered speech with the canonical transcript as optional QA, but delivery cannot depend on Whisper.

Signals

GitHub stars
229
Forks
10
Last commit
Sep 2026
Advanced
Item type
skill
Key
conference-video
Source
github.com/yaxin9luo/autodesign