Content Pipeline

Content Pipeline

Transform one idea into a complete multi-platform content package — a high-engagement LinkedIn post, a 1200×627 cover image, a casual Skool community post, and a premium carousel — all from a single input, run as four sequential stages.

When to Use This Skill

Trigger this skill when the user wants to:

• Repurpose one idea across LinkedIn and Skool
• Run a full content pipeline from a single topic
• Create a "content package" for a post
• Distribute content across multiple platforms at once
• Save time by writing a LinkedIn post, cover, and Skool post in one shot

Trigger phrases:

• "Run the content pipeline on [topic]"
• "Create a LinkedIn + Skool package for [idea]"
• "Repurpose this for LinkedIn and Skool"
• "Make a content package about [topic]"
• "Turn this into a full post package"

Pipeline Overview

[Topic / Idea / Key Points]
            │
            ▼
┌────────────────────────────────────┐
│ Stage 1: LinkedIn Post             │
│   • Hook + re-hook                 │
│   • Body + single takeaway         │
│   • Soft CTA                       │
│   • Repost + Follow lines          │
│   • Hashtags                       │
└────────────────────────────────────┘
            │  linkedin-post.md
            ▼
┌────────────────────────────────────┐
│ Stage 2: Cover Image               │
│   • 1200×627 SVG (1.91:1)          │
│   • Central safe zone              │
│   • Core insight as hero           │
│   • Subtle branding                │
│   • + text prompt for AI tools     │
└────────────────────────────────────┘
            │  cover.svg + cover-prompt.md
            ▼
┌────────────────────────────────────┐
│ Stage 3: Skool Post                │
│   • 30–40% shorter                 │
│   • Casual peer tone               │
│   • No hashtags                    │
│   • Tool/tip/insight leads         │
│   • Bold closing question          │
└────────────────────────────────────┘
            │  skool-post.md
            ▼
┌────────────────────────────────────┐
│ Stage 4: Carousel                  │
│   • Delegates to /carousel-creator │
│   • Pre-collected intake (no       │
│     re-prompting)                  │
│   • Premium SVG slides             │
│   • Caption + exports              │
│   • Outputs land in the SAME       │
│     folder as Stages 1–3           │
└────────────────────────────────────┘
            │  slides/, caption.md, exports
            ▼
[Four deliverables, one input, one folder]

Inputs

Required:

• Topic or idea — The core insight, news, tip, or concept to publish

Optional (gathered during the intake if not provided):

• Key points or outline — 2–5 bullet points or notes to weave into the post
• Tone preference — Urgent, educational, or inspirational (auto-inferred if missing)
• Target audience — Who the post is for (defaults to AI/automation practitioners)
• Tools, prompts, frameworks — Specific AI tools, prompt templates, or systems the post should mention

Outputs

All saved to a date-wise folder in the current working directory using YYYYMMDD-HHMM (real current date/time, computed at intake so all four stages share the same folder):

YYYYMMDD-HHMM/
├── linkedin-post.md         # Stage 1: Title + full post (caption + content + CTAs + hashtags)
├── cover.svg                # Stage 2: 1200×627 SVG cover image
├── cover-prompt.md          # Stage 2: Detailed prompt for Midjourney / DALL-E / Flux
├── skool-post.md            # Stage 3: Casual Skool community post
├── slides/                  # Stage 4: SVG carousel slides (from /carousel-creator)
│   ├── {slug}-slide-1.svg
│   └── ...
├── caption.md               # Stage 4: Carousel caption (from /carousel-creator)
├── {slug}.pdf               # Stage 4: Carousel export
├── {slug}.mp4               # Stage 4: Carousel export
└── {slug}-hyperframes.mp4   # Stage 4: Carousel export

Why a folder: Each stage produces a distinct deliverable. Bundling them in one folder makes the package easy to share, archive, or re-render. Stage 4 is delegated to /carousel-creator and the subagent is responsible for landing all carousel output into the same YYYYMMDD-HHMM/ folder Stages 1–3 already use.

Workflow

Step 0: Intake

Before generating anything, gather the following. Compute the timestamp TS = YYYYMMDD-HHMM once at the start of intake and use it for all four stages — this keeps every stage's output in the same folder.

Content intake (used by Stages 1–3)

1. Topic or idea — If not provided in the argument, ask. Never invent a topic.
2. Key points — Ask for 2–5 bullet points or supporting material, or extract them from the topic.
3. Tone — Default to "educational" unless the topic implies urgency, controversy, or inspiration.
4. Tools / frameworks — Ask if the post should mention specific AI tools, prompts, or systems.

Carousel intake (used by Stage 4)

These are passed to the carousel-creator subagent so it can skip the carousel's own intake questions.

5. Platform — Instagram (1080×1350, 4:5) or LinkedIn (1080×1080, 1:1). Default: LinkedIn to match the post platform.
6. Handle — The CTA handle. Default: @devengoratela (matches the LinkedIn Follow CTA).
7. Audience — Defaults to the same audience inferred for the LinkedIn post.
8. Brand colors — Optional. If provided, pass to the carousel. Otherwise the carousel-creator's premium defaults apply (which already match the cover's dark navy + LinkedIn blue accent).
9. Slide count — Optional. If not provided, let the carousel-creator decide based on topic complexity (default range: 6–8).

If the user provides minimal input (just a topic), make reasonable inferences for all fields and proceed. Note inferred choices inline in the LinkedIn post output (e.g., "(tone: educational, platform: LinkedIn, handle: @devengoratela — say so if you want any of this changed)").

Stage 1: LinkedIn Post

Role: Senior LinkedIn Content Strategist. Your job is a high-engagement, mobile-readable, professional post designed to drive likes, comments, and shares — and funnel interested readers into the Practical AI Skool community.

Hook (lines 1–2)

• Line 1: under 8 words. This is the only line visible before "...see more" on mobile.
• Line 2: a punchy re-hook that earns the click-to-expand.
• Both lines must stop the scroll. No "Today I want to talk about…"

Body

• Short paragraphs. White space between them. No walls of text.
• Emojis at the end of logical sentences (professional, not decorative).
• Adopt a human-to-peer voice.
• Avoid AI slop: delve, landscape, unlock, tapestry, navigate, realm, leverage, in today's fast-paced world, in conclusion, game-changer, revolutionize.
• One clear takeaway or insight. Don't try to teach five things.

Soft CTA (before the closing lines)

A question or invitation to share experiences. Tone-matched to the post:

• Urgent / provocative post → punchy, direct question
• Educational post → value-driven invitation
• Inspirational post → warm, community-focused prompt

Mandatory closing lines (in this exact order, after the soft CTA, before hashtags)

1. ♻️ Repost — A line emphasizing the article's value and why the reader's network needs to see it.
2. ➕ Follow — A line positioning Deven Goratela (https://www.linkedin.com/in/devengoratela/) as the go-to authority for staying ahead in AI and automation.

The three CTA blocks (soft CTA + Repost + Follow) must all match the article's tone.

Output format for linkedin-post.md

# [Post Title] [relevant emoji]

---

[Hook line 1 — under 8 words]
[Re-hook line 2 — punchy]

[Body — short paragraphs with emojis at the end of sentences]

[Soft CTA — question or invitation]

♻️ [Repost line]
➕ Follow [Follow line positioning Deven Goratela as the AI/automation authority]

[Hashtags on their own line, separated by spaces, 3–5 relevant tags]

Output rules

• Title ends with a relevant emoji.
• No bold formatting anywhere in the post body.
• Hashtags are always included.
• The output must be copy-paste ready. No further editing.

Stage 2: Cover Image

Role: Senior visual designer for a high-performing LinkedIn infographic. Visual reinforcement of the post's core insight.

Specifications

• Dimensions: 1200 × 627 px (1.91:1 widescreen).
• Aspect ratio: 1.91:1.
• Safe zone: Keep all critical content in the center 1000 × 500 px (≈100 px margin on all sides). The image is used both as a shared link preview and as an article header — corners may be cropped on different devices.
• No author photo. Do not render or include any image of the author.
• No tool branding like "LinkedIn Cover Image Generator" or any AI tool name on the image.
• Subtle branding: A small handle (@devengoratela) or wordmark in a corner is fine but must not dominate.

Design system (defaults — override with user brand colors if provided)

SVG layout template

┌─────────────────────────────────────────────────────────────┐
│  ▌                                                          │
│  ▌   [CATEGORY / TOPIC TAG]                                 │
│  ▌                                                          │
│      [CORE INSIGHT — HERO TEXT]                             │
│      [wrapped to 2–3 lines max]                             │
│                                                             │
│      [supporting visual — icon, stat, or shape]            │
│                                                             │
│  @devengoratela                              [year/date]    │
└─────────────────────────────────────────────────────────────┘

Process for cover.svg

1. Read the LinkedIn post from Stage 1.
2. Extract the core insight (the single biggest takeaway, usually 6–12 words). If the hook itself works, use it.
3. Extract the category / topic (e.g., "AI Tools", "Automation", "Career", "Prompting").
4. Build the SVG with the layout above. Use text-anchor="middle" for centered hero text. Wrap hero text into 2–3 lines manually (use <tspan> with x and dy for line breaks).
5. Validate the SVG:

   python3 -c "import xml.etree.ElementTree as ET; ET.parse('cover.svg'); print('Valid')"
   

   Fix any errors and re-save until it parses cleanly.

Process for cover-prompt.md

In parallel with the SVG, write a detailed image generation prompt suitable for Midjourney, DALL-E 3, or Flux. Users can use this to upgrade to a higher-fidelity raster render.

cover-prompt.md template:

# LinkedIn Cover Image Prompt

Use this prompt with Midjourney, DALL-E 3, Flux, or any AI image generator.

---

## Prompt

\```
[Full detailed prompt — subject, style, composition, lighting, palette, typography]
\```

## Specifications

- **Dimensions:** 1200 × 627 px (1.91:1)
- **Aspect ratio:** 1.91:1
- **Safe zone:** Keep all text in the center 1000 × 500 px area (corners may be cropped on mobile link previews)
- **Style:** [e.g., "Modern minimal infographic, dark mode aesthetic"]
- **Color palette:** [hex codes]
- **Typography:** [e.g., "Bold sans-serif, large hero text"]

## Do NOT include

- No photo of the author
- No text that says "LinkedIn Cover Image Generator" or any tool name
- No watermarks
- No logo of any AI tool or platform

Stage 3: Skool Post

Role: Casual content conversion assistant for the Practical AI Skool community. The LinkedIn post is the source material; the Skool post is a peer-to-peer reframe.

Persona

• You sound like a fellow AI enthusiast — casual, curious, genuinely helpful.
• You are NOT a corporate content writer. No polished, formal, or salesy language.
• You understand the Practical AI community values real-world application over hype.

Conversion rules

1. Tone: Casual and practical — peer-to-peer, not guru-to-student.
2. Strip LinkedIn-isms: Remove professional posturing, humble-brags, and "thought leadership" phrases.
3. Length: Cut the LinkedIn post by 30–40%. Punchy and direct.
4. Hashtags: Remove all hashtags.
5. Lead with the tool / tip / insight — not the backstory or hook.
6. Keep intact: Any tools, prompts, tips, or frameworks. Reframe them as "here's what worked for me."
7. "We / us" language: Use occasionally — e.g., "for those of us using AI daily…"
8. No hype / buzzwords: Keep everything grounded and actionable.
9. Tools in bold: Use bold for tool names (e.g., Cursor, Claude Code, n8n).
10. Closing question: End with one strong, open-ended question relevant to AI learners, bolded, to spark discussion.

Output format for skool-post.md

# [Hook — 1 line, casual, curiosity-driven]

[Body — short paragraphs, 1–2 lines each]

[Optional: a tool, prompt, or framework block — preserved from the LinkedIn post, reframed as personal experience]

**[Strong open-ended question to spark discussion among AI learners]**

No "Practical AI Skool" branding in the post body itself. The community is the destination, not a tagline in every post.

Stage 4: Carousel (delegated to /carousel-creator)

Stage 4 invokes the carousel-creator skill to produce a premium Instagram or LinkedIn carousel. Reusing the carousel-creator means we don't duplicate its design system, content strategy, and export pipeline — the subagent simply runs the skill with pre-collected intake info and lands the output in the parent pipeline's folder.

Delegation pattern

Spawn a subagent using the Task tool with subagent_type: "general-purpose". The subagent's task prompt is self-contained and includes:

1. Pre-collected intake — topic, key points, tone, platform, handle, audience, brand colors, slide count (from Step 0).
2. Parent folder path — {cwd}/{TS}/ — the same folder Stages 1–3 saved to.
3. Existing files — the subagent must know that linkedin-post.md, cover.svg, cover-prompt.md, skool-post.md already exist in the parent folder.
4. Output directive — "Save all carousel output (slides/, caption.md, PDF, MP4, Hyperframes MP4) into the parent folder {TS}/. Do not create a separate timestamped folder."

Subagent task prompt template

You are running Stage 4 of the content-pipeline skill. Your job is to invoke the
`carousel-creator` skill with the pre-collected intake below, then ensure all
carousel output lands in the parent pipeline's folder.

PARENT FOLDER: {cwd}/{TS}/
This folder already contains:
- linkedin-post.md
- cover.svg
- cover-prompt.md
- skool-post.md

PRE-COLLECTED INTAKE (all fields are provided — do NOT re-ask the user):
- Topic: {topic}
- Key points: {key_points}
- Tone: {tone}
- Platform: {platform}
- Handle: {handle}
- Target audience: {audience}
- Brand colors: {brand_colors_or_default}
- Slide count: {slide_count_or_default}

STEPS:
1. Invoke the `carousel-creator` skill (via the Skill tool). The skill's intake
   will be skipped because all fields are provided above.
2. The carousel-creator will create its own timestamped folder based on "actual
   current date and time". In most cases this matches {TS}, so the folder is
   shared naturally. If a minute boundary was crossed during the parent
   pipeline's run, the folder name will differ by one minute (e.g., 20260616-1649
   vs 20260616-1650). Detect this with `ls -la {cwd}/` and compare timestamps.
3. If the carousel-creator's folder is a DIFFERENT folder than {TS}, move all
   its contents into {TS}/:
   - mv {TS_carousel}/* {TS}/
   - rmdir {TS_carousel}
4. Run the carousel-creator's export scripts (PDF, MP4, Hyperframes MP4) per
   its own SKILL.md instructions. Confirm all four files end up in {TS}/.
5. Report back with the final list of files in {TS}/.

Do NOT ask the user any intake questions — every field is pre-collected.

Why a subagent (not inline)

• Context cleanliness — The carousel-creator's intake, design system, and export logic would otherwise clutter the main content-pipeline context.
• Pre-collected intake — The subagent prompt has all the fields, so the carousel-creator's intake step is a no-op. The user is never asked the same question twice.
• Folder reconciliation — The subagent can detect timestamp drift between the parent pipeline's TS and the carousel-creator's auto-generated folder, and move files to reconcile.

Why "actual current date and time" is fine

The carousel-creator's instruction to use "actual current date and time" is a default, not a hard constraint. Because:

• content-pipeline computes TS at intake (Step 0)
• Stage 4 runs within seconds to minutes of intake
• The carousel-creator's invocation typically lands in the same minute
• If a minute boundary is crossed, the subagent reconciles with a mv (Step 3 above)

In 99% of runs, the timestamps match and no mv is needed.

Output from Stage 4

After Stage 4, the parent folder contains everything from Stages 1–3 plus:

• slides/{slug}-slide-{n}.svg — one SVG per slide
• caption.md — carousel caption (also usable as a bonus LinkedIn post variant)
• {slug}.pdf — multi-page PDF export
• {slug}.mp4 — MP4 slideshow (5 s/slide)
• {slug}-hyperframes.mp4 — Ken Burns + cross-dissolve cinematic MP4

Stage Handoffs

Each stage must consume the previous stage's output:

If a stage needs clarification that the user did not provide, make a reasonable inference and note it. Do not stop the pipeline to ask.

Quality Checklist

Before reporting done, verify:

LinkedIn post:

• Hook is under 8 words
• Re-hook is punchy and earns the expand
• Single clear takeaway
• No AI slop words (delve, landscape, unlock, etc.)
• Soft CTA is a question or invitation
• Repost + Follow lines present in correct order
• Tone of all CTAs matches the article
• 3–5 hashtags, no bold in the body

Cover image:

• SVG is 1200×627 with viewBox="0 0 1200 627"
• Critical content sits inside the center 1000×500 safe zone
• No author photo, no tool-name branding on the image
• Subtle @devengoratela handle visible somewhere
• SVG validates with xml.etree.ElementTree.parse
• Companion cover-prompt.md exists with full prompt + do-not-include list

Skool post:

• 30–40% shorter than the LinkedIn post
• No hashtags
• No LinkedIn-isms (humble-brags, "thought leader" framing)
• Tool names in bold where they appear
• Ends with one bolded open-ended question
• Body reads like a peer talking, not a brand broadcasting

Carousel (delegated to /carousel-creator):

• All five files (slides/, caption.md, .pdf, .mp4, -hyperframes.mp4) sit inside {TS}/
• At least 5 SVG slides in slides/
• CTA slide includes @devengoratela
• No separate timestamped folder exists alongside {TS}/ (timestamp drift reconciled via mv)
• User was NOT re-prompted for carousel intake (all fields pre-collected)

Final Behavior

After all four stages complete:

1. Confirm every file is saved to the YYYYMMDD-HHMM/ folder (Stages 1–3 by the main agent, Stage 4 by the carousel-creator subagent).
2. List the saved files with one-line descriptions.
3. Remind the user:
   • The LinkedIn post is copy-paste ready.
   • The SVG cover can be opened in any browser or imported into Figma.
   • The cover-prompt.md can be pasted into Midjourney / DALL-E for a higher-fidelity render.
   • The Skool post is ready to drop into the community.
   • The carousel slides/, caption.md, PDF, MP4, and Hyperframes MP4 are all in the same folder — ready to upload to Instagram / LinkedIn.

Do NOT ask for permission between stages. Run all four in sequence from a single input.