Linkedin Launch Video logo

Linkedin Launch Video

Organization
cognyai
linkedin-launch-video

Produce a LinkedIn-native 1:1 (or 16:9) launch video using HyperFrames. Caption-first, sound-off, B2B register, anti-corporate-jargon. Optionally hand off to LinkedIn Ads to launch as a sponsored content campaign with ICP-aligned targeting.

Overview

Publishercognyai
Repositoryclaude-code-marketing-skills
Skill namelinkedin-launch-video
Stars
111
Forks
15
Bundled files
2
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by cognyai on GitHub. Read the source before you install it.

Installation

Install the Linkedin Launch Video AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cognyai/claude-code-marketing-skills/tree/main/skills/linkedin-launch-video
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cognyai/claude-code-marketing-skills.git /tmp/claude-code-marketing-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-marketing-skills/skills/linkedin-launch-video .claude/skills/linkedin-launch-video
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Linkedin Launch Video in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Linkedin Launch Video on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Linkedin Launch Video is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

LinkedIn Launch Video

Produce a LinkedIn-native launch video using HyperFrames.

LinkedIn's autoplay is muted, the feed is scrolled in 2-second chunks, and the audience is allergic to either extreme — too corporate (sounds like a 2010 SaaS press release) or too TikTok (looks unprofessional in front of buyers). This skill targets the middle: caption-driven, conversational founder/operator voice, real numbers, no jargon.

Usage

/linkedin-launch-video https://example.com/launch — pulls context from a launch page /linkedin-launch-video "we're shipping inbound CRM scoring for B2B sales teams" — short brief /linkedin-launch-video — interview the user

Works with

Making the video needs no accounts. Publishing is optional, and every publish call asks first.

JobPrimaryAlso answers itWhat differs
Run as sponsored contentLinkedIn Ads—Created PAUSED; the creative is a DRAFT until the user activates it
Post organicallyLinkedIn Organic (company Page)X OrganicPersonal profiles still out-reach Pages; X takes the same MP4 (≤ 512 MB)
What past video posts did (optional)LinkedIn Organic tool_get_organization_posts + tool_get_post_statistics—Use to pick length and hook style before scripting

Prerequisites

bash
node --version            # ≥ 22
ffmpeg -version | head -1 # ≥ 6

Steps

1. Gather product context AND ICP context

LinkedIn videos die when the audience is "everyone". They work when the first frame names the role.

Try sources in order:

1a. Local file — .agents/product-marketing-context.md or .claude/product-marketing-context.md.

1b. Cogny MCP context tree — if the cogny MCP server is connected:

mcp__cogny__get_context_tree_overview
mcp__cogny__search_context query="ICP" / query="<product>"
mcp__cogny__read_context_node node_id="…"

The tree usually contains the actual ICP definition (role, seniority, industry, ARR band) and the most-recent shipped feature — both load-bearing for LinkedIn-grade specificity. Check it before public scraping.

1c. Public web — WebFetch the URL only if 1a/1b are empty.

Then ask:

  1. Who is this for, by role and seniority? ("Heads of Demand Gen at B2B SaaS, $5–50M ARR")
  2. What is the expensive problem they have right now? (cost, time, headcount)
  3. What's the proof point — a customer name, a metric, a screenshot, a benchmark?
  4. Who is the on-screen voice? (Founder? Operator? Customer? No-face / text-only is also valid on LinkedIn.)
  5. What's the conversion goal? (Signup, demo, follow, comment, reshare)

If the role / proof / goal are vague, push back before writing. LinkedIn ROI lives or dies on these three.

1.5 Capture brand identity

Make this look like the user's brand. LinkedIn's audience is buyers — generic stock styling reads as "untrusted vendor".

Ask for one of: site URL, repo path with tailwind.config.* / CSS variables, an existing brand-kit.json, or manual input (3 hex + font + voice). Save the result as brand-kit.json in the HyperFrames project root.

For full schema, extraction patterns, and voice → composition mapping see references/brand-identity.md.

LinkedIn-specific brand notes:

  • Avoid LinkedIn blue (#0a66c2) as the brand accent — it merges with the platform UI and the video reads as a chrome screenshot.
  • Avoid the same accent the platform overlays use — LinkedIn places white profile names with drop shadow on the top-15%; ensure your accent reads under that.
  • Display fonts are fine here (unlike Reddit) — LinkedIn is the channel where serif headlines and editorial typography land best.

The composition template reads --bg, --fg, --primary, --accent, --font-display as CSS variables — wire them from your kit and the template's structure stays.

2. Pick the format

LinkedIn-idiomatic video formats that work in 2025–2026:

FormatWhen to useStructure
Founder-to-cameraAuthentic launchesFounder face + burned-in captions; explain the why, the how, the proof
Numbers carouselData-led launchesStat → context → stat → context → stat → "want the breakdown? comment X"
Customer quoteMid/late-stage social proofReal screenshot of customer message → product clip → CTA
"Here's what we shipped"Feature releasesPlain title → 3 short clips with captions → release-notes-style CTA
Anti-pattern teardownThought leadership / category creation"Most teams do X. It doesn't work because Y. Here's what we built instead."

Pick one. Confirm with the user.

3. Write the script (LinkedIn grammar)

  • Total length: 30–75 seconds. The sweet spot is 45s. Anything over 90s gets clipped.
  • Hook (0–3s): name the role, name the problem. "If you run paid for a B2B SaaS, this 30-second clip is for you."
  • Captions are the script. LinkedIn auto-captions exist but are sloppy — burn your own in, max 8 words per card, sentence case, no all-caps.
  • No music, or extremely subtle ambient. Voiceover optional but captions are the source of truth.
  • No "thrilled to announce", no "game-changer", no "next-generation". Read it out loud — if it sounds like a press release, rewrite.
  • Concrete CTA: "Comment WAITLIST", "Tap the link to try it", "DM me 'demo'", or "Follow [name] for more". "Learn more" is dead.

Hand the beat sheet back. Wait for confirmation.

4. Scaffold the HyperFrames project

bash
npx -y hyperframes@latest init <product-slug>-linkedin --non-interactive --resolution square
cd <product-slug>-linkedin

Use --resolution landscape instead for the 16:9 variant (step 5). There is no --yes flag; --non-interactive is what disables the prompts.

5. Compose the video (1:1 default, 16:9 alternative)

LinkedIn's feed is dominated by square (1:1). 16:9 plays but takes ~25% less vertical space, hurting scroll-stop rate. 9:16 is supported but rarely the right call unless the asset will be repurposed for IG Reels later.

Default to 1080×1080 (1:1). Use 1920×1080 (16:9) only if the user is also embedding on a website / running in YouTube pre-roll.

Reference composition: see references/composition-template.html.

LinkedIn-specific styling rules:

  • Type: 56–84px. Bigger than Reddit (because of LinkedIn's tighter line-height in feed), smaller than TikTok.
  • Color: a single brand accent over white or off-white. Avoid LinkedIn-blue itself — feels like the platform UI bled in. Black/white with one warm accent reads as confident and not-stock.
  • Motion: deliberate. 0.4–0.6s tweens, no bounce, no flashy easing. Buyers read this as "competent".
  • Caption block: pin captions to the bottom 25% with a faint scrim if there's any background imagery. Top 15% should remain clean — that's where LinkedIn overlays profile name on autoplay previews.
  • Numbers > adjectives: every claim needs a number. If you can't put a number on a card, cut the card.

6. Lint & render

Check dependencies first:

bash
npx hyperframes doctor

If it reports FFmpeg missing, stop before rendering and tell the user to install it (brew install ffmpeg on macOS, sudo apt install ffmpeg on Debian/Ubuntu). Meanwhile, npx hyperframes snapshot captures key frames as PNGs without FFmpeg, so they can review the cards.

bash
npx hyperframes lint
npx hyperframes render --output launch.mp4

7. Sanity check

  • First card names the role or the problem within 3 seconds?
  • Every claim has a number?
  • Captions readable on a phone with sound off?
  • No buzzwords (excited, thrilled, revolutionary, game-changing, leverage, synergy, unlock, supercharge, next-gen)?
  • Length 30–75s?

If any check fails, edit and re-render.

8. (Optional) Hand off to LinkedIn Ads

If the user wants to run this as paid sponsored content, LinkedIn's edge is B2B targeting precision. Use it.

The MCP needs the video at a public URL. On Cloud, call mcp__cogny__mcp__cogny-image-gen__tool_request_upload_url and run the returned curl to get a public_url (asks first); otherwise ask the user for a hosted link. Then, after the user approves each write:

mcp__cogny__mcp__LinkedIn_Ads__tool_list_ad_accounts                       # note the currency
mcp__cogny__mcp__LinkedIn_Ads__tool_search_targeting_entities(facet_urn: "urn:li:adTargetingFacet:industries", query: "<industry>")
mcp__cogny__mcp__LinkedIn_Ads__tool_get_audience_counts(ad_account_id, targeting_criteria: {...})   # confirm reach before launch

mcp__cogny__mcp__LinkedIn_Ads__tool_create_campaign_group(ad_account_id, name, status: "PAUSED")
mcp__cogny__mcp__LinkedIn_Ads__tool_create_campaign(
  ad_account_id, campaign_group_id, name,
  objective_type: "VIDEO_VIEW" | "WEBSITE_VISIT" | "LEAD_GENERATION",
  daily_budget_amount: "<amount the user stated>", daily_budget_currency: "<account currency>",
  targeting_criteria: {...}, status: "PAUSED"
)
mcp__cogny__mcp__LinkedIn_Ads__tool_upload_video(ad_account_id, video_url: "<public MP4 URL, ≤ 200 MB>", owner_urn: "urn:li:organization:<page id>")
mcp__cogny__mcp__LinkedIn_Ads__tool_create_creative(
  ad_account_id, campaign_id, author_organization_urn: "urn:li:organization:<page id>",
  commentary, image_urn: "<urn:li:video:… from upload_video>", destination_url, call_to_action_type,
  status: "DRAFT"
)

Notes:

  • Campaign group and campaign are PAUSED; the creative is DRAFT (LinkedIn can't create creatives paused). The user activates manually after reviewing.
  • Budget amounts are strings in the account's currency ("100.00" = $100).
  • Use get_audience_counts before create_campaign — LinkedIn won't let an audience smaller than 300 ship.
  • For LEAD_GENERATION, you need a Lead Gen Form ID — that's not creatable via this MCP, so create it in Campaign Manager first.

If the user has run /crm-icp-analysis and /linkedin-micro-campaigns, this skill completes the loop by producing the actual creative those targeted campaigns will run.

For organic posting: hand the user launch.mp4 and recommend posting from a personal profile (or both personal + company page). Personal-profile organic reach on LinkedIn beats company-page reach by roughly 5–10x.

If LinkedIn Organic is connected, offer to post or schedule it on the company Page (asks first, needs the public URL): mcp__cogny__mcp__LinkedIn_Organic__tool_schedule_post(scheduled_for, text, author: "<org URN from tool_list_organizations>", video_url, video_title), or tool_create_post with the same fields to post now. If X Organic is connected, offer mcp__cogny__mcp__X_Organic__tool_upload_media(file_url) then tool_create_post(text, media_ids) (posts publicly at once, so confirm the text first).

Output format

When you finish, print:

  1. Path to the rendered MP4
  2. The beat sheet
  3. The format chosen and why it fits the ICP
  4. (If applicable) the LinkedIn Ads campaign group / campaign (PAUSED) and creative (DRAFT) IDs, plus the audience size estimate
  5. (If applicable) the scheduled or published organic post IDs

Common mistakes

  1. Corporate intro — "At [Company], we believe…". Cut it. Open with the role/problem.
  2. No number on the proof card — abstract claims ("better", "faster") are filtered out. Buyers want numbers.
  3. TikTok-style frenzy — fast cuts and kinetic text read as junior on LinkedIn. Slow down.
  4. Buzzword bingo — "leverage", "unlock", "revolutionary", "game-changer". Buyers ignore videos with this language.
  5. Generic CTA — "Learn more" is dead. Use "Comment X", "DM me", "Tap link".
  6. Ignoring the muted-autoplay reality — assume zero sound. Captions or it's invisible.

Related

  • /tiktok-launch-video — same pattern for TikTok
  • /reddit-launch-video — same pattern for Reddit
  • /video-to-gif — convert MP4 to a feed-ready GIF (LinkedIn comments don't render GIFs, but DMs do)
  • /linkedin-micro-campaigns — pair the video with ICP-targeted campaigns
  • /linkedin-ads-audit — diagnose existing LinkedIn campaigns before launching new creative

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Linkedin Launch Video AI skill do?

Produce a LinkedIn-native 1:1 (or 16:9) launch video using HyperFrames. Caption-first, sound-off, B2B register, anti-corporate-jargon. Optionally hand off to LinkedIn Ads to launch as a sponsored content campaign with ICP-aligned targeting.

Why use Linkedin Launch Video on TypingMind?

Because you install it once and use it with any model. Linkedin Launch Video is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Linkedin Launch Video in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cognyai/claude-code-marketing-skills/tree/main/skills/linkedin-launch-video. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Linkedin Launch Video?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Linkedin Launch Video?

As many as you like. As long as a model supports skills, you can use Linkedin Launch Video with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Linkedin Launch Video AI skill free?

It is published on GitHub by cognyai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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