القائمة
Video content planning. Writes narration scripts, storyboards, shot lists, and asset checklists. Saves plan to marketing/video-plan.md.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | video-creator |
| description | Video content planning. Writes narration scripts, storyboards, shot lists, and asset checklists. Saves plan to marketing/video-plan.md. |
| metadata | {"author":"runedev","version":"0.3.0","layer":"L3","model":"sonnet","group":"media","tools":"Read, Write, Edit, Glob, Grep"} |
Video content planning for product demos and marketing. Writes narration scripts with timing marks, creates scene-by-scene storyboards, defines shot lists, and lists required assets. Saves the complete production plan to a file. This skill creates PLANS for video production — not actual video files.
marketing (L2): demo/explainer video scriptslaunch (L1): product demo videosNone — pure L3 utility.
Accept input from calling skill:
topic — what the video is about (e.g. "Rune plugin demo", "Feature X walkthrough")audience — who will watch (e.g. "developers", "non-technical founders", "existing users")duration — target length in seconds (e.g. 60, 120, 300)platform — where it will be published: youtube | twitter | tiktok | loom | internaloutput_path — where to save the plan (default: marketing/video-plan.md)Derive constraints from platform:
Write a narration script with timing marks. Before writing a single line, apply the Narration Craft principles below — a script the viewer HEARS lives or dies on the opening and the flow, not the shot list.
Structure:
Format each section:
[00:00] HOOK
Narration: "..."
On screen: [what viewer sees]
[00:05] SETUP
Narration: "..."
On screen: [what viewer sees]
Create a scene-by-scene breakdown:
For each scene:
Example:
Scene 3: Live demo — install command
Duration: 12s
Visual: Terminal window, typed command "npm install -g @rune/cli", output scrolling
Narration: "Install in seconds with one command."
Transition: cut
Define exactly what needs to be recorded or shown:
Categorize by type:
Format:
Shot 1 — Screen recording
URL: https://myapp.com/dashboard
Action: Click "New Project" → fill form → click Create
Duration: ~8s
Shot 2 — Terminal
Command: npm install -g @rune/cli && rune init my-project
Expected output: [describe what should appear]
Duration: ~10s
List every asset required before recording can begin:
Use Write to save the complete video plan to marketing/video-plan.md (or the specified output_path):
# Video Plan: [topic]
- **Platform**: [platform]
- **Target Duration**: [duration]s
- **Audience**: [audience]
- **Created**: [date]
## Script
[full timestamped script from Step 2]
## Storyboard
[scene-by-scene breakdown from Step 3]
## Shot List
[all shots from Step 4]
## Assets Needed
[checklist from Step 5]
## Platform Notes
[constraints and tips for the target platform]
Then output a summary to the calling skill:
## Video Plan Created
- File: [output_path]
- Scenes: [count]
- Shots: [count]
- Estimated recording time: [n] minutes
- Assets to prepare: [count] items
### Next Steps
1. Prepare assets listed in the plan
2. Record shots in order from the shot list
3. Edit using the storyboard as reference
A demo script is HEARD by a person, not read off a slide. These principles separate an engaging script from generic voiceover — apply them in Step 2, before writing any line.
The 9 principles:
Named + numbered "weapons". Give each differentiator a title and a number ("Weapon 01/02"). Mine the 2-3 NON-OBVIOUS specifics (a regex, a guard, an algorithm, a fallback) — one precise surprising mechanism beats a generic capability list.
Connectors between scenes. Each scene after the first opens with a linguistic connector referring back ("The core of it is…", "Specifically…", "But note…") so the whole video plays as ONE monologue, not N telegraphic captions read in a row. Read the full script aloud in sequence — if it sounds like disconnected soundbites, rewrite.
Auto-fail patterns — reject the script if any appear:
When narration will be synthesized by a TTS engine (AI voiceover, not a human reading),
the spoken narration and the on-screen text are SEPARATE channels — one is heard, one
is read. Optimize each independently; never feed a raw slug, number, or symbol into TTS
and hope the voice guesses right. (The Vietnamese examples below illustrate the pattern;
apply the same phonetic + numbers-as-words substitution for whatever language the target
TTS engine speaks.)
Numbers → spoken words (many neural TTS engines can misread bare digits — VN examples):
| Form | TTS misreads | Write as |
|---|---|---|
| Version decimal | GPT 5.5 → "năm rưỡi" | GPT năm chấm năm |
| Stat decimal | 82.7% | tám mươi hai phẩy bảy phần trăm |
| Spec | 200MP | hai trăm megapixel |
| Price | $5 / 21 triệu | năm đô / hai mươi mốt triệu đồng |
| Multiplier / percent | 2x / 30% | gấp đôi / ba mươi phần trăm |
English/brand names → phonetic in narration, exact spelling on screen:
| Term | narration (heard) | display (read) |
|---|---|---|
| README | ruýt my | README |
| ffmpeg | ép ép em peg | ffmpeg |
| GitHub / repo | git hâb / rề pô | GitHub / repo |
| API / GPT | ây pi ai / gí pi tí | API / GPT |
Strip from spoken narration: emoji, URLs (say "github chấm com gạch…"), symbols (→ & % $ # / @), slash-commands (say "the plugin install command"), file extensions mid-sentence (say "the YAML file"), camelCase identifiers, ellipsis … and em-dash — (TTS misreads them — split into two short sentences). End every sentence with . or ? for a natural pause.
Keep the jargon, natural spoken register. Write the way a knowledgeable friend SAYS it — but keep the standard technical term ("commit", "endpoint", "prompt" stay in their usual form; a hard translation sounds wrong and loses meaning). Only translate when the local word is the one people actually use.
Production notes for a spoken video (if it will actually be produced, not just planned):
This skill creates PLANS for video production. Actual recording and editing must be done by a human or a dedicated screen recording tool.
Video Plan saved to marketing/video-plan.md with script, storyboard, shot list, assets checklist, and platform notes. Summary report with scene/shot counts and estimated recording time. See Step 6 Report above for full template.
Known failure modes for this skill. Check these before declaring done.
| Failure Mode | Severity | Mitigation |
|---|---|---|
| Platform constraints not applied (e.g., Twitter max 140s exceeded) | HIGH | Step 1: derive constraints from platform immediately — they constrain everything downstream |
| Missing CTA section in script | MEDIUM | CTA (last 10s) is required in every script — no exceptions regardless of duration |
| Not saving to file (only verbal output) | HIGH | Constraint 3 + Step 6: Write to output_path is mandatory — verbal only = no persistence |
| Promising an actual deliverable video file | MEDIUM | Note explicitly: this skill creates a PLAN — actual recording is done by a human |
| Flat catalogue opener ("Today we'll look at…") instead of a pain-first hook | HIGH | Narration Craft #1: open on the viewer's biggest pain — an opener that names no problem loses the scroll in 2 seconds |
| Raw slugs/numbers/symbols left in narration for TTS ("README", "82.7%", "5.5") | HIGH | Voiceover section: rewrite spoken narration phonetically + numbers-as-words; keep exact spelling only on the display channel |
| Script reads as N disconnected soundbites | MEDIUM | Narration Craft connectors: each scene after the first opens referring back — read the whole script aloud before declaring done |
~500-1500 tokens input, ~500-1000 tokens output. Sonnet for script quality.
Design system reasoning. Maps product domain to style, palette, typography, and platform-specific patterns. Generates .rune/design-system.md as the shared design contract for all UI-generating skills.
Performance regression gate. Detects N+1 queries, sync-in-async, missing indexes, memory leaks, and bundle bloat before they reach production. Ranks findings by Cost Impact Hierarchy (architecture > data transfer > compute > DB > caching) so fix priority maps to actual unit-cost reduction.
Code quality review — patterns, security, performance, correctness. Finds bugs, suggests improvements, triggers fix for issues found. Escalates to opus for security-critical code.
Gathers N independent, decorrelated perspectives across model families (external CLIs when present, subagents when not) and arbitrates inline. Use when a decision needs genuine debate — not same-model echo — for critique, review, or judge calls. Honest about degradation: never claims 'consensus' from a single model family.
Environment-aware pre-flight check. Use when starting work in a new environment, switching machines, or when 'works on my machine' bugs surface. Validates OS, runtime versions, installed tools, port availability, env vars, and disk space BEFORE coding starts. Like sentinel but for the environment, not the code.
Creative ideation and solution exploration. Generates multiple approaches with trade-offs, uses structured frameworks (SCAMPER, First Principles), and hands off to plan for structuring.