Draft voice-tuned LinkedIn post variants from a free-form brief. Reads a personal voice guide (generated via generate-voice-guide), produces 2–5 variants with distinct framings, applies LinkedIn-specific defaults (arrow bullets, "why this matters" beat, 150–500 words), and self-checks against the voice guide's banned phrases before returning.
npx gooseworks install --all # then, in Claude Code, Cursor, or Codex: /gooseworks use the create-linkedin-content skill
Draft LinkedIn post variants that sound like a real human practitioner, not a LinkedIn thought-leader persona. Reads a voice guide the user has already generated (or prompts to create one), produces multiple framings of the same idea, and saves each variant as its own markdown file with frontmatter.
This is an agent-executed skill — the agent does the drafting and self-check inline. No Python script.
Mirrors create-x-content structurally; differences are marked ★.
/create-linkedin-content --brief "New open-source CLI that turns Figma files into React components. Called figma2react. Free, MIT licensed."Or interactively:
/create-linkedin-content| Flag | Required | Default |
|---|---|---|
--brief | Yes (asked interactively if missing) | — |
--variants | No | Skill decides based on brief richness (2–5) |
--voice-guide | No | Resolved via chain below |
--output | No | ./content/YYYY-MM-DD-<topic-slug>/ |
--topic | No | Derived from brief |
Resolve in this order, stop at first hit:
--voice-guide <path> flag~/.goose-skills/config.json → voice_guides.linkedin~/.goose-skills/voice-guides/voice-linkedin.md (default path)/generate-voice-guide --platforms linkedin now to create one (recommended)Apply these unless the voice guide explicitly says otherwise:
→) for workflow steps — this is LinkedIn-native1️⃣ 2️⃣ 3️⃣ allowed sparingly for installation/quickstart type postsSame as create-x-content Phase 1 — load voice guide, extract banned phrases, hook patterns, format rules, dos/don'ts, examples.
Same 2–5 decision rubric. LinkedIn briefs often warrant fewer variants than X because LinkedIn posts are longer and the audience expects more narrative coherence — 3 strong framings usually beats 5.
Framings tuned for LinkedIn (subset of the X framings, plus a few LinkedIn-native ones):
| Framing | Structure | When to use |
|---|---|---|
builder-story ★ | "I built X. Here's why. Here's what I learned." | LinkedIn-native — builder stories outperform tactical posts here |
product-launch ★ | Clear hook + 2-step quickstart + link | New tool/product announcements |
problem-first | Open with the pain, then solution | Universal |
ecosystem-map | Curated list of N related tools/companies | Landscape posts |
contrarian-insight | "Your X might be worth more than Y" | Opinion pieces with a fresh take |
workflow-tutorial | Arrow-bulleted step-by-step, with numbers | Tactical how-tos (denser than X version) |
Same 4 checks as create-x-content:
Plus LinkedIn-specific:
5. Arrow-bullet check — if the post uses lists, are they → style (or numbered emojis), matching the LinkedIn convention?
6. "Why this matters" check — does the post explain the stakes, or does it just state the facts? Add a "why this matters" beat if missing.
7. No corporate tone — does it sound like a press release? If yes, rewrite to sound like a human practitioner.
File naming (the linkedin- prefix distinguishes from X variants when they live in the same folder):
linkedin-<letter>-<framing-slug>.mdExamples: linkedin-a-builder-story.md, linkedin-b-product-launch.md.
Frontmatter:
---
id: <topic-slug>-li-<letter>
platform: linkedin
format: standard | long
topic: <slug>
framing: <framing-slug>
status: draft
---Print output directory, file list, framing summary, suggested next step.
<output>/linkedin-<letter>-<framing>.md per variantBuilder story brief:
/create-linkedin-content --brief "Built a CRM for my AI agents using just markdown files and Claude Code. No Salesforce, no HubSpot. Works better than both."→ 3 variants (builder-story, contrarian-insight, workflow-tutorial)
Launch brief:
/create-linkedin-content --brief "Launching goose-aeo — open-source CLI that measures your brand's visibility on AI search engines like ChatGPT, Perplexity, Gemini. npm install, three commands to run."→ 3 variants (product-launch, problem-first, workflow-tutorial)
generate-voice-guide skill (for creating one when missing)→) for workflow steps — this is LinkedIn-native1️⃣ 2️⃣ 3️⃣ allowed sparingly for installation/quickstart type postsAssemble an expert/educator motion-graphic LISTICLE video ad from a config — a spoken authoritative voiceover carries a numbered listicle while N web-animated hyperframe beats (HTML plus the Web Animations API, one branded design system of alternating tiles, big hero numerals, and glass-pill callouts) are rendered frame-by-frame via Playwright and anchored to the VO's word-level timestamps, periodic color-graded B-roll windows give visual breath, and captions burn ONLY inside those B-roll windows (2-word chunks, ASS Format header carrying a Name field so none drop) with the VO mixed under a low music bed. This is the FREE deterministic assembly stage (Playwright beat render plus ffmpeg concat plus window-masked caption burn plus VO-and-music mix plus final composite) — the VO, the music bed, and the stock B-roll come from create-vo-elevenlabs, create-music-elevenlabs, and media-proxy. Use for the vo-anchored-motion-listicle format.
Assemble a stop-motion hand-swatch-cycle product-demo ad from a config — a sequence of still PLATES (one hand swiping a single-barrel cosmetic across a cream skin-patch, the barrel + swatch changing per plate while the hand, background, crop, and lighting stay locked) is PNG→mp4 loop-encoded at each plate's own stop-motion hold (fast motion frames 150–250ms, per-shade ~380ms, hero beats 1100–1800ms), concat-demuxed with HARD cuts into a silent master, closed on a Playwright HTML-rendered branded end card (serif tagline + sans subtitle + real logo SVG over a hero BG, never AI-rendered text), and muxed with a pre-sourced music track playing under the end card with a fade tail (no VO). This is the FREE deterministic assembly stage (loop-encode + concat-demux + end-card render + music mux); the master-anchor plate, shade plates, and end-card BG come from create-image-gpt-image-fal and the track from create-music-elevenlabs. Use for the stopmotion-hand-swatch-cycle format.
Assemble a split-screen creator ad from a config — a two-zone vertical composite where a supplied AI-creator lip-sync take fills the BOTTOM ~48% while real 16:9 product/demo clips run uncropped in the TOP ~52%, each top clip contain-fit with a darkened blurred cover-scale fill of the same clip (never black bars), a 3px brand-color divider between the zones, the creator slice cover-fit per the per-scene VO timing, scenes hard-concatenated with the body audio being the concatenated creator VO slices, an end card held on the last sharp frame ~3s, then the ASSEMBLED cut transcribed with local Whisper (not the raw VO — concat drops inter-scene silence) and word-level captions burned in the chosen style. This is the FREE deterministic assembly + caption stage (two-zone composite + blurred fill + divider + hard-concat + end card + captions); the VO comes from create-vo-elevenlabs, the anchor from create-image-gpt-image-fal, and the whole-VO lip-sync from a paid VEED Fabric 1.0 take (a no-atom upstream input). Use for the split-screen-creator format.