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Memstack Automation Content Pipeline

Community
cwinvestments
memstack-automation-content-pipeline

Use this skill when the user says 'content pipeline', 'content automation', 'auto-publish', 'repurpose content', 'multi-platform publishing', or needs end-to-end content workflow from ideation through cross-platform formatting and publishing. Do NOT use for single social media posts or individual blog posts.

Overview

Publishercwinvestments
Repositorymemstack
Skill namememstack-automation-content-pipeline
Stars
425
Forks
45
Bundled files
Instructions only
LicenseMIT
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Memstack Automation Content Pipeline 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/cwinvestments/memstack/tree/master/skills/automation/content-pipeline
  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/cwinvestments/memstack.git /tmp/memstack
mkdir -p .claude/skills
cp -r /tmp/memstack/skills/automation/content-pipeline .claude/skills/memstack-automation-content-pipeline
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Memstack Automation Content Pipeline 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 Memstack Automation Content Pipeline 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 Memstack Automation Content Pipeline 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.

Content Pipeline: Automating content workflow...

Automates end-to-end content workflows from ideation through draft, review, approval, cross-platform formatting, scheduling, and publishing with CMS integration and image optimization.

Activation

When this skill activates, output:

Content Pipeline: Automating content workflow...

Then execute the protocol below.

Context Guard

ContextStatus
User says "content pipeline", "content automation", "auto-publish"ACTIVE
User says "repurpose content" or "multi-platform publishing"ACTIVE
User wants to automate content creation through distributionACTIVE
User wants a single blog postDORMANT: use Blog Post
User wants a single social media postDORMANT, use Twitter Thread or TikTok Script

Common Mistakes

MistakeWhy It's Wrong
"Same content on every platform"Each platform has its own format, tone, and audience expectations. Repurpose, don't copy-paste.
"Automate quality away"Automation handles formatting and scheduling, not editorial judgment. Keep human review in the loop.
"No content calendar"Publishing without a schedule leads to feast-or-famine posting. Consistency beats volume.
"Skip image optimization"Unoptimized images slow page load and fail platform size requirements. Automate resizing.
"Publish and forget"Monitor engagement within 24-48 hours. Boost winners, learn from underperformers.

Protocol

Step 1: Gather Pipeline Requirements

If the user hasn't provided details, ask:

  1. Content types: what do you produce? (blog, newsletter, social, video, podcast)
  2. Platforms: where do you publish? (website, Twitter/X, LinkedIn, Instagram, YouTube, email)
  3. Frequency: how often? (daily, 3x/week, weekly)
  4. Team: who's involved? (writer, editor, designer, social manager)
  5. CMS: what do you use? (WordPress, Ghost, Notion, Webflow, headless CMS)
  6. Current process: what's manual today that should be automated?

Step 2: Design Pipeline Stages

[Ideation] → [Draft] → [Review] → [Approve] → [Format] → [Schedule] → [Publish] → [Monitor]

Stage definitions:

StageOwnerInputOutputAutomation Level
IdeationContent leadKeyword research, trending topics, audience questionsContent briefSemi-auto (AI-assisted topic generation)
DraftWriterContent briefRaw draft (Markdown/Docs)Manual (AI-assisted)
ReviewEditorRaw draftEdited draft with feedbackManual
ApproveContent leadEdited draftApproved for publishingManual (checklist-gated)
FormatPipelineApproved contentPlatform-specific versionsFully automated
SchedulePipelineFormatted contentQueued posts with dates/timesFully automated
PublishPipelineScheduled postsLive content across platformsFully automated
MonitorMarketingPublished contentEngagement metricsSemi-auto (dashboard)

Step 3: Content Repurposing Matrix

Define how one piece of content becomes many:

Source→ Blog Post→ Twitter Thread→ LinkedIn→ Newsletter→ Instagram
Blog postOriginalKey points (5-10 tweets)Summary + insightsFeatured articleQuote card + carousel
VideoTranscript → postKey quotesBehind-the-scenesRecap + linkClips (15-60s)
PodcastShow notesSoundbite quotesEpisode summaryWeekly roundupAudiogram
NewsletterExpanded articleThread from sectionCross-postOriginalHighlight card

Repurposing rules:

  • Each platform version should feel native (not like a cross-post)
  • Adjust tone: Twitter (punchy, direct), LinkedIn (professional, storytelling), Instagram (visual, emotional)
  • Adjust length: Twitter (280 chars/tweet), LinkedIn (1300 chars optimal), Instagram (2200 chars max)
  • Add platform-specific elements: hashtags (Instagram), mentions (Twitter), links (LinkedIn)

Step 4: Image Optimization Pipeline

Platform image specs:

PlatformSizeAspect RatioMax File SizeFormat
Blog (hero)1200×6301.91:1200KBWebP (JPEG fallback)
Twitter1200×67516:95MBPNG/JPEG
LinkedIn1200×6271.91:15MBPNG/JPEG
Instagram (feed)1080×10801:18MBJPEG
Instagram (story)1080×19209:168MBJPEG
Newsletter600×3002:1100KBPNG/JPEG
Open Graph1200×6301.91:1200KBPNG/JPEG

Automated image processing:

bash
# Using sharp (Node.js) or ImageMagick
# From one source image, generate all platform variants:

sharp(sourceImage)
  .resize(1200, 630, { fit: 'cover' })
  .webp({ quality: 80 })
  .toFile('blog-hero.webp');

sharp(sourceImage)
  .resize(1080, 1080, { fit: 'cover' })
  .jpeg({ quality: 85 })
  .toFile('instagram-square.jpg');

sharp(sourceImage)
  .resize(1080, 1920, { fit: 'cover' })
  .jpeg({ quality: 85 })
  .toFile('instagram-story.jpg');

Step 5: Scheduling Strategy

Optimal posting times (general: adjust to your analytics):

PlatformBest DaysBest Times (ET)Frequency
BlogTue-Thu10 AM1-3x/week
Twitter/XMon-Fri8 AM, 12 PM, 5 PM1-3x/day
LinkedInTue-Thu7-8 AM, 12 PM3-5x/week
InstagramMon, Wed, Fri11 AM, 1 PM3-5x/week
NewsletterTue or Thu9-10 AM1x/week
YouTubeThu-Sat2-4 PM1-2x/week

Content calendar template:

markdown
## Week of [Date]

| Day | Blog | Twitter | LinkedIn | Newsletter | Instagram |
|-----|------|---------|----------|-----------|-----------|
| Mon | none | [Thread from Friday's blog] | none | none | [Quote card] |
| Tue | [New post: Topic] | [3 promo tweets] | [Post: summary] | [Weekly send] | none |
| Wed | none | [Engagement thread] | none | none | [Carousel] |
| Thu | none | [Tips thread] | [Article share] | none | [Behind-scenes] |
| Fri | [New post: Topic] | [3 promo tweets] | [Post: summary] | none | [Quote card] |

Step 6: CMS Integration Patterns

Headless CMS workflow (API-based):

typescript
// Publish to CMS via API
async function publishToCMS(content: {
  title: string;
  body: string;
  slug: string;
  featuredImage: string;
  tags: string[];
  publishAt?: Date;
}): Promise<string> {
  const response = await cmsClient.post('/posts', {
    title: content.title,
    content: content.body,
    slug: content.slug,
    featured_image: content.featuredImage,
    tags: content.tags,
    status: content.publishAt ? 'scheduled' : 'published',
    published_at: content.publishAt?.toISOString(),
  });
  return response.data.url;
}

Social media scheduling (via Buffer/Hootsuite API or native):

typescript
async function scheduleToSocial(posts: SocialPost[]): Promise<void> {
  for (const post of posts) {
    await bufferClient.post('/updates/create', {
      profile_ids: [post.profileId],
      text: post.content,
      media: post.imageUrl ? { photo: post.imageUrl } : undefined,
      scheduled_at: post.scheduledAt.toISOString(),
    });
  }
}

Step 7: Monitoring & Optimization

Engagement tracking (24-48 hours post-publish):

MetricBlogTwitterLinkedInNewsletter
Views/ImpressionsPage viewsImpressionsImpressionsOpens
EngagementTime on pageLikes + repliesReactions + commentsClick rate
ConversionCTA clicksLink clicksLink clicksReply rate
Share/ViralSocial sharesRetweetsRepostsForwards

Content scoring formula:

Score = (Engagement Rate × 40%) + (Conversion Rate × 40%) + (Shares × 20%)
  • A-tier (top 20%): Repurpose aggressively, boost with ads, create sequel content
  • B-tier (middle 60%): Standard distribution, note what worked
  • C-tier (bottom 20%): Analyze why it underperformed, adjust future topics

Output Format

markdown
# Content Pipeline: [Brand/Product Name]

## Pipeline Stages
[Stage diagram and definitions from Step 2]

## Repurposing Matrix
[From Step 3: source → platform transformations]

## Image Specs
[Platform-specific sizes from Step 4]

## Content Calendar
[Weekly template from Step 5]

## CMS & Social Integration
[API patterns from Step 6]

## Monitoring Dashboard
[Metrics and scoring from Step 7]

Completion

Content Pipeline: Complete!

Platforms: [Count] ([list])
Content types: [Count]
Pipeline stages: 8 (ideation → monitor)
Publishing frequency: [X pieces/week across platforms]
Automation level: [X/8 stages automated]

Next steps:
1. Set up CMS API access and social scheduling tool
2. Create image templates for each platform
3. Build the first week's content calendar
4. Automate the Format → Schedule → Publish stages
5. Review engagement data weekly and adjust

Level History

  • Lv.1: Base: 8-stage pipeline (ideation through monitoring), content repurposing matrix (blog/video/podcast → 5 platforms), platform image specs with automated processing, optimal posting times, content calendar template, CMS integration patterns (headless API, social scheduling), engagement monitoring with content scoring formula. (Origin: MemStack Pro v3.2, Mar 2026)

Frequently asked questions

What does the Memstack Automation Content Pipeline AI skill do?

Use this skill when the user says 'content pipeline', 'content automation', 'auto-publish', 'repurpose content', 'multi-platform publishing', or needs end-to-end content workflow from ideation through cross-platform formatting and publishing. Do NOT use for single social media posts or individual blog posts.

Why use Memstack Automation Content Pipeline on TypingMind?

Because you install it once and use it with any model. Memstack Automation Content Pipeline 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 Memstack Automation Content Pipeline in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cwinvestments/memstack/tree/master/skills/automation/content-pipeline. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Memstack Automation Content Pipeline?

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 Memstack Automation Content Pipeline?

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

Is the Memstack Automation Content Pipeline AI skill free?

Yes. It is published on GitHub by cwinvestments under the MIT license. 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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