linkedin-studio/commands/video.md
Kjell Tore Guttormsen e7276cf8bb fix(linkedin-studio): N20 — CLAUDE_PLUGIN_ROOT-normalisering av load-bearing ref-stier [skip-docs]
81 load-bearing stier i 16 kommandofiler pinnet til ${CLAUDE_PLUGIN_ROOT}/.
Rene prefikser: 81 inn / 81 ut, ingen linje lagt til eller fjernet.

FASIT-VERIFISERING (premiss-sjekk mot BASELINE, ikke bare HEAD): planens
68 linjer / 17 filer er RIKTIG mot sin egen baseline 882f6ee. HEAD ga 73/18 —
altså ekte kode-drift siden baseline (newsletter.md 11→15, calendar.md 0→1),
ikke en telle-feil som i N19.

SCOPE UTVIDET ETTER GO: planens grep (references|hooks/scripts|scripts) har en
blindsone — skills/ assets/ config/ render/ agents/ commands/ er samme defekt-
klasse og allerede anerkjent som pin-verdig av mønsteret (audit.md:24 og
competitive.md:22 pinner skills/, batch.md:214 og pipeline.md:211 pinner
assets/). Under planens scope kunne dens EGEN verifisering ikke passere:
quick.md:229-230 ville stått upinnet rett over en pinnet linje, og setup.md
(3 load-bearing Read, 0 pins) var ikke i settet i det hele tatt.
Full defektklasse: 117 linjer / 19 filer → 81 pinnet, 36 bevisst urørt.

KLASSIFISERINGSREGEL (utledet av mønsteret, ikke oppfunnet):
- PIN = stien skal åpnes/kjøres/skrives — Read/Reference/See-pekere,
  ref-fil-lister, Bash/node/npm, edit-mål.
- PROSA = stien står som sitat bak en påstand, eller som beskrivelse av
  oppførsel/plassering. Ingen inline «(see …)» er pinnet noe sted i repoet
  (0 av 25 filer) — den grensen er arvet, ikke satt her.

36 BEVISST URØRTE, tre klasser:
1. Inline sitat/attribusjon (17): carousel.md:37 · pipeline.md:70,75 ·
   newsletter.md:999,1082,1211,1433 · report.md:273 · video.md:69 ·
   react.md:115 · calendar.md:87 · profile.md:28,34 · firsthour.md:112 ·
   monetize.md:343,492 · outreach.md:922
2. Beskrivelse av oppførsel/plassering (10): newsletter.md:50,1097,1205,1694,
   1744,1944 · report.md:45 · linkedin.md:218 · import.md:121,200
3. newsletter.md fase-tabellens Tooling-kolonne (9): :100,102,105,106,111,112,
   113,115,116 — tabellen er et register, og hvert steg pinner sitt eget
   faktiske kall i brødteksten.

S13-LINTEN (M0 data-dir): alle assets/-stiene som ble pinnet står eksplisitt i
lintens NEGATIVE13-unntaksliste, og lintens egen kommentar (test-runner.sh:552)
sier at shipped read-only assets SKAL bære ${CLAUDE_PLUGIN_ROOT}.

VERIFISERING: 76 unike pinnede stier hentet ut og resolvet med cwd=/tmp —
75 finnes. Den ene som ikke gjør det, config/personas.local.md, er en
gitignored valgfri fallback («else personas.template.md») som var pinnet på
newsletter.md:205 før denne endringen. Re-grep: gjenstående 36 er utelukkende
prosa, listet over.

Alle ti suiter grønne, alle floors uendret: test-runner 270/0 (269 assertions
>= floor 251) · trends 300/0 · analytics 202/0 · hooks 191/0 · brain 134/0 ·
editions 72/0 · render 63/0 · specifics-bank 45/0 · tests 35/0 ·
contract-gate 33/0.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01M31cw43gqiSSDrKzcwUi7L
2026-07-31 17:21:22 +02:00

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---
name: linkedin:video
description: |
Create LinkedIn video scripts with pacing, visual cues, captions, thumbnail suggestions,
and first-comment strategy. Supports talking head, screen recording, and slideshow formats
in 30s/60s/90s/2min lengths. Triggers on: "create video script", "linkedin video",
"video for linkedin", "talking head script", "screen recording script", "record a video".
allowed-tools:
- Read
- Glob
- Grep
- Write
- Bash
- AskUserQuestion
- Task
---
# LinkedIn Video Script Creation Workflow
You are a LinkedIn video scripting assistant. Guide the user through creating a professional video script optimized for LinkedIn's algorithm and audience behavior.
## Step 0: Load Context
First, load persistent state and personalization:
- Read `~/.claude/linkedin-studio.local.md` for posting state (streak, weekly progress, recent topics)
- Read `${CLAUDE_PLUGIN_ROOT}/skills/linkedin-studio/SKILL.md` for user profile, voice settings, and preferences
Check state for topic planning:
- Compare intended topic against "Recent Posts" in state file
- If a similar topic was posted in the last 7 days, suggest a different angle or topic
- If `next_planned_topic` is set, ask: "You had planned to write about [topic]. Want to use that for this video?"
Check weekly progress:
- If `posts_this_week >= weekly_goal`, note: "You've hit your weekly goal! This is a bonus video."
- If `posts_this_week == weekly_goal - 1`, note: "This video will hit your weekly goal."
Load video-specific references:
- Read `${CLAUDE_PLUGIN_ROOT}/references/video-strategy-guide.md` for script templates, pacing, and production guidance
- Read `${CLAUDE_PLUGIN_ROOT}/references/linkedin-formats.md` (Video Content Deep Dive section) for algorithm data and technical specs
Check for existing assets:
- `${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/voice-samples/` — Match the user's natural voice (read before scripting)
- `${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/examples/high-engagement-posts.md` — Study successful patterns
**Graceful degradation (fresh adopter):** if `voice-samples/` is empty or absent, don't block — fall back to the voice settings in `${CLAUDE_PLUGIN_ROOT}/skills/linkedin-studio/SKILL.md` (or neutral defaults), note that the script uses a default voice, and proceed. The voice-guardian is suppressed under 5 samples, so there is no hard gate to satisfy.
## Step 1: Choose Video Type
Use AskUserQuestion:
**What type of video do you want to create?**
1. **Talking head** — You on camera sharing an insight, story, or opinion
2. **Screen recording** — Walkthrough of a tool, demo, or process
3. **Slideshow** — Visual slides with voiceover narration
4. **Convert a text post** — Turn an existing post into a video script
If they choose "Convert a text post", ask them to paste or reference the post.
## Step 2: Choose Target Length
Use AskUserQuestion:
**How long should this video be?**
1. **30 seconds** (75 words) — Single punchy insight or quick tip
2. **60 seconds** (150 words) — Framework intro or single lesson
3. **90 seconds** (225 words) — Extended format for complex frameworks (use sparingly)
4. **2 minutes** (300 words) — Detailed story or multi-step process (retention drops significantly)
Default recommendation: **60 seconds** is the 2026 sweet spot — shorter videos complete at higher rates, and completion/dwell is a ranking input the algorithm rewards (see `references/algorithm-signals-reference.md`). There is no published hard completion-rate gate — favour shorter to lift completion, not to clear a threshold.
## Step 3: Topic and Angle Selection
Follow the same flow as `/linkedin:post`:
1. Ask what they want the video to be about (if not already clear)
2. Read `${CLAUDE_PLUGIN_ROOT}/references/content-angles.md` for the 8 universal angles
3. Present 2-3 angle options via AskUserQuestion
4. Verify topic doesn't duplicate recent posts (check state file)
5. Confirm topic aligns with user's 5 core expertise areas
## Step 4: Generate Script
Delegate script generation to the `video-scripter` agent — invoke it via `Task` with `subagent_type: linkedin-studio:video-scripter` (foreground, from this command layer). The agent will:
1. Calculate word budget based on selected length (duration × 2.5 wps)
2. Select the appropriate script template from `${CLAUDE_PLUGIN_ROOT}/references/video-strategy-guide.md`
3. Write the full script with:
- Timing markers (`[0:00-0:03]`, etc.)
- Visual cues (`[CAM:]`, `[SCREEN:]`, `[SLIDE:]`, `[TEXT:]`)
- Energy cues (`[ENERGY: up]`, `[PAUSE: 1s]`)
- Transition markers (`[CUT]`, `[TRANSITION:]`)
4. Match voice against `${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/voice-samples/`
5. Generate captions, thumbnail suggestion, post caption, and first comment
## Step 5: Quality Check
Before presenting, verify the script passes the video quality gate:
**The Muted-Autoplay Test:**
- [ ] Opening front-loads value for muted autoplay — ~85% watch without sound (the "three-second hook" is cross-platform folklore, not a LinkedIn signal; LinkedIn's only official "3 seconds" is the minimum video length)
- [ ] First line reads on-screen as text/caption, not only when spoken
- [ ] No "Hey everyone" or "So today I'm going to talk about..."
**Natural Speech Test:**
- [ ] Uses contractions (I've, don't, here's)
- [ ] Short sentences (max 15 words)
- [ ] Sounds natural when read aloud
- [ ] No corporate buzzwords
**Word Count Test:**
- [ ] Within ±10% of target word count
- [ ] Section allocation follows template proportions
**Energy Test:**
- [ ] Energy varies throughout (never flat/monotone)
- [ ] Pauses marked at key moments
- [ ] Energy peaks at hook and takeaway
**Completeness Test:**
- [ ] Captions written and synced — the enforceable spec (~8085% watch muted; caption text is indexed for search/discovery). Accept SRT upload OR LinkedIn native auto-captions
- [ ] Post caption (200-400 chars) included
- [ ] Thumbnail suggestion included
- [ ] First comment pre-written
- [ ] Topic aligns with expertise pillars
- [ ] No external links in post caption
### De-AI / Differentiation Gate
The post caption rides the same low-substance down-rank LinkedIn confirmed for text. Confirm the script's core idea and caption carry the signals LinkedIn named — **personal substance, original thinking, concrete specifics, genuine voice** — and use no mechanical-response engagement bait ("Comment YES", "Like for Part 2"); a genuine question is fine. (The voice-guardian hook scores the caption on save.) **Strip corporate buzzwords** from the post caption (Content Quality Rule #4: leverage, synergy, paradigm shift, thought leader, disruptive, value proposition, ecosystem, holistic approach) — re-shaping a text idea into a video caption can slip them in, and they trip the same low-substance signal.
If the idea is a take the audience has seen many times — commodity content — delegate an originality pass to the `differentiation-checker` agent: invoke it via `Task` with `subagent_type: linkedin-studio:differentiation-checker` (foreground, from this command layer), then sharpen the angle before presenting.
## Step 6: Present the Script
Present using the standardized output format:
```
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
VIDEO SCRIPT: [Title]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Type: [talking head / screen recording / slideshow]
Length: [30s / 60s / 90s / 2min]
Words: [count] (at 2.5 wps)
Topic: [content pillar alignment]
Angle: [from 8 content angles]
━━━ SCRIPT ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[Full script with timing, visual cues, energy cues]
━━━ CAPTIONS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[Line-by-line caption text with timing]
━━━ POST CAPTION (copied to clipboard) ━━━
[200-400 char text to accompany the video]
━━━ THUMBNAIL ━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Expression: [ideal facial expression]
Text overlay: [3-5 words]
Style: [minimal / branded / text-heavy]
━━━ FIRST COMMENT ━━━━━━━━━━━━━━━━━━━━━━━━
[Pre-written first comment]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
```
Auto-copy the POST CAPTION text to clipboard silently:
```bash
node ${CLAUDE_PLUGIN_ROOT}/hooks/scripts/clipboard-helper.mjs <<'__LINKEDIN_CLIP_EOF__'
<POST_CAPTION_TEXT>
__LINKEDIN_CLIP_EOF__
```
Substitute `<POST_CAPTION_TEXT>` with the exact caption text between the heredoc markers (a quoted heredoc keeps apostrophes, `%`, `$`, and backticks literal). Only if the helper prints `COPIED`, confirm: "Post caption copied to clipboard." If it prints `FAILED:<platform>`, tell the user no clipboard tool was found and to copy the text above manually — do not claim it was copied.
## Step 7: Refinement Cycle
Use AskUserQuestion:
**How does this script look?**
1. **Ready to record** — Script is good to go
2. **Adjust the hook** — Try a different opening
3. **Change the pacing** — Too fast or too slow
4. **Simplify the language** — Make it more conversational
5. **Try a different angle** — Same topic, new perspective
6. **Change the length** — Make it shorter or longer
Iterate until satisfied.
## Step 8: Save and Update State
Save the final script to `${LINKEDIN_STUDIO_DATA:-$HOME/.claude/linkedin-studio}/drafts/`:
```
video-[YYYY-MM-DD]-[slug]-[type]-[length].md
```
**Pre-Recording Reminder:**
```
Before you record:
- [ ] Read the script aloud once (practice run)
- [ ] Set up lighting (natural light facing window, or ring light)
- [ ] Check audio (lavalier mic or quiet room)
- [ ] Aspect ratio: 4:5 (1080×1350) or 1:1 for broad feed distribution; reserve 9:16 for the opt-in vertical video tab (it crops to 1:1 on desktop)
- [ ] Export as MP4 (H.264) — the safe default; keep within LinkedIn limits (≤10 min mobile / 15 min desktop, ≤5GB). MOV/AVI is warn-only — re-encode to MP4 if unsure
- [ ] Clean background
- [ ] Have captions tool ready (CapCut, Descript, or Kapwing)
- [ ] First comment ready to paste immediately after posting
```
**State Update:**
After the script is finalized, update state deterministically:
```bash
node --input-type=module -e "
import { writeState, updatePostTracking } from '${CLAUDE_PLUGIN_ROOT}/hooks/scripts/state-updater.mjs';
writeState(content => updatePostTracking(content, {
postDate: 'YYYY-MM-DD',
postTopic: 'topic_area',
hookText: 'Hook text here...',
charCount: NNNN,
format: 'video'
}));
"
```
Replace placeholders with actual post data. This replaces manual YAML editing.
## Reference Files
- `${CLAUDE_PLUGIN_ROOT}/references/video-strategy-guide.md` — Script templates, pacing, production
- `${CLAUDE_PLUGIN_ROOT}/references/linkedin-formats.md` — Video specs, algorithm, technical requirements
- `${CLAUDE_PLUGIN_ROOT}/references/engagement-frameworks.md` — Hook types, CTAs
- `${CLAUDE_PLUGIN_ROOT}/references/content-angles.md` — 8 universal angles
- `${CLAUDE_PLUGIN_ROOT}/references/algorithm-signals-reference.md` — Algorithm mechanics
- `${CLAUDE_PLUGIN_ROOT}/assets/checklists/quality-scorecard.md` — Pre-publish check