video-shortform
Short-form video generation skill — 3-10 second clips for product reveals, motion teasers, ambient loops. Defaults to Seedance 2 but works the same with Kling 3 / 4, Veo 3 or Sora 2. Output is one MP4 saved to the project folder. When the workspace also ships an interactive-video / hyperframes skill, prefer composing several short shots into a single timeline rather than one long monolithic clip.
What this skill does
# Video Shortform Skill
Short-form (≤ 10s) is the sweet spot for current text-to-video models —
they're great at one **shot** with one **idea**, weaker at multi-cut
narratives. Plan one shot per call.
Special case: `hyperframes-html` is **not** a photoreal text-to-video
model. It's a local HTML-to-MP4 renderer. For that model, do not roleplay
cinematography or "real-world" camera physics. Treat the brief as a motion
design card / title-frame / product interstitial, ask at most one
clarifying question, then dispatch immediately.
## Resource map
```
video-shortform/
├── SKILL.md
└── example.html
```
## Workflow
### Step 0 — Read the project metadata
`videoModel`, `videoLength` (seconds), `videoAspect`. These are
hard-locks — clamp the prompt to whatever the chosen model supports
(Seedance 2 caps at 10s; Kling 4 supports up to 10s + image-to-video;
Veo 3 supports 8s with audio).
### Step 1 — Plan the shot
Write the shotlist BEFORE calling the model:
| Slot | Content |
|---|---|
| Subject | What's in frame? |
| Camera | Static / pan / push-in / orbit? |
| Lighting | Key direction + temperature |
| Motion | What moves, at what pace? Subject motion vs camera motion. |
| Sound | Ambient bed? (only if the model supports audio) |
Normally, show this to the user as a one-sentence plan before
dispatching — they can redirect cheaply.
For `hyperframes-html`, skip the extra pre-dispatch narration once the
user has answered the discovery form. Collapse the plan into the actual
generation prompt and dispatch immediately.
### Step 2 — Compose the prompt
Use the format the upstream model prefers (Seedance: motion + camera +
mood; Kling: subject + camera + style; Veo: subject + cinematography +
sound). Bind the project's `videoAspect` and `videoLength` directly to
the API parameters; never put them in prose.
For `hyperframes-html`, write a concise motion-design brief instead of a
camera-realism prompt. Focus on subject, layout, palette, motion
character, and overall tone. Do not spend turns narrating environment
checks, missing side files, or "I am about to dispatch" status updates.
### Step 3 — Dispatch via the media contract
Use the unified dispatcher — do **not** call provider APIs by hand:
```bash
"$OD_NODE_BIN" "$OD_BIN" media generate \
--project "$OD_PROJECT_ID" \
--surface video \
--model "<videoModel from metadata>" \
--aspect "<videoAspect from metadata>" \
--length <videoLength seconds> \
--output "<short-slug>-<seconds>s.mp4" \
--prompt "<assembled shot prompt from Step 2>"
```
The command prints one line of JSON: `{"file": {"name": "...", ...}}`.
The bytes land in the project; the FileViewer plays it automatically.
### Step 4 — Hand off
Reply with: shot summary, the filename returned by the dispatcher, and
one sentence on what to try if the user wants a variation.
For `hyperframes-html`, keep the reply especially short: what was
rendered, the filename, and one concrete variation idea.
## Hard rules
- One shot per turn. Multi-shot timelines belong in a hyperframes /
interactive-video skill, not here.
- Match `videoAspect` exactly — re-renders are slow.
- Never ship a video without saving the file — the user expects
something to play in the file viewer.
- When the underlying model fails (NSFW filter, content policy,
timeout), report the error verbatim. Don't silently retry.
- Do not claim a render has been "sent", "started", or "is running"
unless you have already called `"$OD_NODE_BIN" "$OD_BIN" media generate`.
Related in Image & Video
watch
IncludedWatch a video (URL or local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or Whisper API fallback), and hands the result to Claude so it can answer questions about what's in the video.
physical-ai-defect-image-generation
IncludedUse when the user wants to orchestrate defect image generation, run associated setup, or handle outputs on OSMO. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint.
accelint-react-best-practices
IncludedReact performance optimization and best practices. ALWAYS use this skill when working with any React code - writing components, hooks, JSX; refactoring; optimizing re-renders, memoization, state management; reviewing for performance; fixing hydration mismatches; debugging infinite re-renders, stale closures, input focus loss, animations restarting; preventing remounting; implementing transitions, lazy initialization, effect dependencies. Even simple React tasks benefit from these patterns. Covers React 19+ (useEffectEvent, Activity, ref props). Triggers - useEffect, useState, useMemo, useCallback, memo, inline components, nested components, components inside components, re-render, performance, hydration, SSR, Next.js, useDeferredValue, combined hooks.
elevenlabs-agents
IncludedBuild conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication
humanizer
IncludedHumanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
generating-mermaid-diagrams
IncludedSalesforce architecture diagrams using Mermaid with ASCII fallback. Use this skill when generating text-based diagrams for Salesforce architecture, OAuth flows, ERDs, integration sequences, or Agentforce structure. TRIGGER when: user says "diagram", "visualize", "ERD", or asks for sequence diagrams, flowcharts, class diagrams, or architecture visualizations in Mermaid. DO NOT TRIGGER when: user wants PNG/SVG image output (use generating-visual-diagrams), or asks about non-Salesforce systems.