| name | hub |
| description | KTG content marketing pipeline. Takes a written blog post and runs the full publishing workflow: repurpose for all platforms, generate hero image, SEO and AI citation optimisation, then pause for green-light before publishing to all channels via Composio. Local-first: uses Ollama for text tasks where quality allows, cloud for image gen and live data. Use when user says "hub", "/hub", "publish this", "run the pipeline", "post this everywhere".
|
| user-invokable | true |
| argument-hint | <post-file-path> [--cloud] |
| disable-model-invocation | false |
| metadata | {"author":"ktg","version":"1.2.0"} |
Hub — KTG Content Marketing Pipeline
Drop a post file. Get it published everywhere.
Local-First Routing
| Task | Local (Ollama) | Cloud (Skill tool) | Default |
|---|
| Repurpose | Ministral:latest (13.5B) | blog-repurpose | Local |
| SEO validation | Qwopus:latest (9B) | blog-seo-check | Local |
| GEO scoring | Qwopus:latest (9B) | blog-geo | Local |
| Schema JSON-LD | Ministral:latest (13.5B) | seo-schema | Local |
| Page SEO audit | Qwopus:latest (9B) | seo-page | Local |
| Technical SEO | Qwopus:latest (9B) | seo-technical | Local |
| Image alt text | QwenVL:latest (8.2B) | — | Local |
| Embeddings | qwen3-embedding:latest | — | Local |
| Hero image | — | blog-image → banana | Cloud |
| Live SERP data | — | seo-dataforseo | Cloud |
| Publish | — | Composio MCP | Cloud |
Override: Pass --cloud to skip local and use cloud skills for all text tasks.
Ollama Invocation Pattern
curl -s http://localhost:11434/api/tags | python3 -c "import sys,json; [print(m['name']) for m in json.load(sys.stdin)['models']]"
curl -s http://localhost:11434/api/generate \
-d '{"model":"Ministral:latest","prompt":"<prompt>","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])"
curl -s http://localhost:11434/api/chat \
-d '{"model":"Ministral:latest","messages":[{"role":"user","content":"<prompt>"}],"stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['message']['content'])"
curl -s http://localhost:11434/api/embeddings \
-d '{"model":"qwen3-embedding:latest","prompt":"<text>"}' \
| python3 -c "import sys,json; print(len(json.load(sys.stdin)['embedding']))"
Context window: Ministral 13.5B = ~32k tokens. For posts >10k words, chunk into 8k-token segments.
Plugin Map
| Step | Skill Name | Scope | Command | Arguments |
|---|
| Repurpose (cloud) | blog-repurpose | User (~/.agents/skills/) | Skill tool | prompt with file path + platforms |
| Images | blog-image | User (~/.agents/skills/) | Skill tool | generate <topic> |
| Images (alt) | banana | Project (.claude/skills/) | Skill tool | generate <prompt> |
| GEO audit (cloud) | blog-geo | User (~/.agents/skills/) | Skill tool | prompt with file path |
| SEO audit (cloud) | seo-page | User (~/.agents/skills/) | Skill tool | <url> or file path |
| Technical SEO (cloud) | seo-technical | User (~/.agents/skills/) | Skill tool | <url> or file path |
| Schema (cloud) | seo-schema | User (~/.agents/skills/) | Skill tool | <url> or file path |
| SEO check (cloud) | blog-seo-check | User (~/.agents/skills/) | Skill tool | prompt with file path |
Step 0 — Validate input
Parse $ARGUMENTS for a file path. If none provided:
Usage: /hub <path-to-post.md>
Example: /hub wiki/content/mirage-post/post.md
Read the post file. Extract:
- Title — from frontmatter
title: or first H1
- Slug — kebab-case title for output file naming
- Platform — detect from frontmatter
platform: if present (default: generic blog)
Report: Running KTG hub pipeline on: <title>
Step 1 — Repurpose
Default (local): Generate variants via Ollama Ministral:latest.
Read the post file into memory. If >8k words, extract key points (title, thesis, 3 main arguments, 2 key stats, CTA) and pass the summary instead of full text.
Run 5 Ollama calls in sequence (or parallel via Agent tool):
curl -s http://localhost:11434/api/generate \
-d '{"model":"Ministral:latest","prompt":"Write a Medium article (800-1200 words, professional tone, discussion prompt at end) based on this blog post:\n\n<post-content-or-summary>\n\nOutput only the article, no preamble.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-medium.md
curl -s http://localhost:11434/api/generate \
-d '{"model":"Ministral:latest","prompt":"Write a Reddit discussion post (authentic tone, r/ClaudeAI format, discussion starter) based on this blog post:\n\n<post-content-or-summary>\n\nOutput only the post, no preamble.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-reddit.md
curl -s http://localhost:11434/api/generate \
-d '{"model":"Ministral:latest","prompt":"Write an X/Twitter thread (hook tweet + 8-15 tweets, engagement CTA, match character limits) based on this blog post:\n\n<post-content-or-summary>\n\nOutput only the thread, one tweet per line, no preamble.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-x-thread.md
curl -s http://localhost:11434/api/generate \
-d '{"model":"Ministral:latest","prompt":"Write a Facebook/Meta post (scannable, key takeaways, CTA) based on this blog post:\n\n<post-content-or-summary>\n\nOutput only the post, no preamble.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-meta.md
curl -s http://localhost:11434/api/generate \
-d '{"model":"Ministral:latest","prompt":"Write a LinkedIn article (professional tone, data-forward, 800-1200 words, discussion prompt) based on this blog post:\n\n<post-content-or-summary>\n\nOutput only the article, no preamble.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-linkedin.md
Cloud fallback (--cloud or if Ollama not running):
Use the Skill tool with name="blog-repurpose":
Read the blog post at <file-path>. Repurpose it for ALL platforms: Medium article, Reddit discussion post, X thread, Meta post, and LinkedIn article. Generate all five variants in one invocation. Match platform-native tone and formatting. Save each variant to the same directory as the post using these exact filenames:
social-medium.mdsocial-reddit.mdsocial-x-thread.mdsocial-meta.mdsocial-linkedin.md
Report: Repurpose complete — 5 variants generated
Step 2 — Images
Generate hero image:
Use the Skill tool with name="blog-image" and pass:
Generate a hero image for a blog post titled "". The post is about <one-sentence summary>. Style: editorial, AI/tech theme, no text overlay. Aspect ratio: 16:9. Save to hero-16x9.png in the post directory.
If blog-image MCP is unavailable, fall back to Skill tool with name="banana":
Generate a hero image for a blog post titled "". The post is about <one-sentence summary>. Style: editorial, AI/tech theme, no text overlay. Aspect ratio: 16:9. Size: 2K. Save to hero-16x9.png in the post directory.
Crop for platforms (ImageMagick — run via Bash):
magick "hero-16x9.png" -resize 1200x627^ -gravity Center -extent 1200x627 "hero-linkedin.png"
magick "hero-16x9.png" -resize 1200x675^ -gravity Center -extent 1200x675 "hero-x.png"
magick "hero-16x9.png" -resize 1080x1080^ -gravity Center -extent 1080x1080 "hero-square.png"
If ImageMagick is not installed, report: "ImageMagick not found — skipping crops. Install with winget install ImageMagick.ImageMagick then re-run."
Report: Images complete — hero + 3 crops
Step 3 — Optimise
Default (local): Run audits via Ollama. All prompts extract the post's frontmatter + first 2000 words + heading structure to stay within context limits.
3a. AI citation / GEO optimisation (local):
curl -s http://localhost:11434/api/generate \
-d '{"model":"Qwopus:latest","prompt":"You are a GEO (Generative Engine Optimization) analyst. Score this blog post for AI citation readiness (ChatGPT, Perplexity, Google AI Overviews).\n\nPost content:\n<post-frontmatter + first 2000 words + all headings>\n\nRate 0-100 on:\n1. Passage-Level Citability (clear 120-180 word answer blocks)\n2. Structural Readability (H1-H2-H3 hierarchy, question headings, lists/tables)\n3. Authority Signals (author byline, dates, sources cited)\n4. Technical Accessibility (AI crawler hints, no JS-gated content)\n5. Freshness (update dates within 30 days)\n\nOutput format:\nGEO Readiness Score: XX/100\nPlatform Breakdown: Google AIO: X/100 | ChatGPT: X/100 | Perplexity: X/100\nTop 5 Changes: 1. ... 2. ... 3. ... 4. ... 5. ...","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > GEO-ANALYSIS.md
3b. SEO audit (local):
curl -s http://localhost:11434/api/generate \
-d '{"model":"Qwopus:latest","prompt":"You are an SEO auditor. Analyze this blog post for on-page SEO and content quality.\n\nPost content:\n<post-frontmatter + first 2000 words + all headings>\n\nScore 0-100 per category:\n- On-Page SEO (title, meta, H1, headings, URL, internal/external links)\n- Content Quality (word count, readability Flesch 60-70, keyword density 1-3%, E-E-A-T)\n- Technical Meta (canonical, OG tags, Twitter Cards, hreflang)\n- Images (alt text, file size, format, dimensions, lazy loading)\n\nOutput: Overall Score: XX/100 with category breakdown and prioritized fixes.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > SEO-ANALYSIS.md
curl -s http://localhost:11434/api/generate \
-d '{"model":"Qwopus:latest","prompt":"You are a technical SEO auditor. This is a static Markdown blog post (not a live site). Audit what CAN be checked from the file:\n\nPost content:\n<post-frontmatter + all headings + links + image refs>\n\nCheck:\n1. Heading hierarchy (no skipped H1->H2->H3)\n2. Internal links (3+ contextual, descriptive anchor)\n3. External links (2+ authoritative, Tier 1-2)\n4. Image alt text (present on all images)\n5. URL slug (lowercase, hyphens, <60 chars)\n6. Canonical hint (if frontmatter has canonical)\n7. OG/twitter card hints (if frontmatter has them)\n8. Mobile readiness (short paragraphs, no tables wider than screen)\n\nOutput: Technical Score: XX/100 with fixes.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" >> SEO-ANALYSIS.md
3c. Schema markup (local):
curl -s http://localhost:11434/api/generate \
-d '{"model":"Ministral:latest","prompt":"Generate valid JSON-LD schema.org markup for this blog post.\n\nPost frontmatter:\n<frontmatter>\n\nPost title: <title>\nAuthor: <author or \"Kevin Tan\">\nPublished: <date>\nModified: <date>\nURL: <canonical or placeholder>\n\nRequired schemas:\n1. Article (or BlogPosting) — headline, author, datePublished, dateModified, image, publisher\n2. Organization — name, url, logo, sameAs\n3. Person (author) — name, url, sameAs\n4. BreadcrumbList — if applicable\n\nOutput ONLY valid JSON-LD inside ```json ... ``` blocks. No commentary.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > schema.json
3d. Post-writing SEO validation (local):
curl -s http://localhost:11434/api/generate \
-d '{"model":"Qwopus:latest","prompt":"Run a post-writing SEO validation checklist on this blog post.\n\nPost content:\n<full post>\n\nChecklist (pass/fail + fix if fail):\n□ Title tag: 40-60 chars, primary keyword in first half, power word\n□ Meta description: 150-160 chars, statistic included, value prop at end\n□ H1: exactly one, matches intent, includes keyword\n□ Heading hierarchy: no skipped levels (H1->H2->H3 only)\n□ Internal links: 3+ contextual, descriptive anchor\n□ External links: 2+ authoritative sources\n□ Canonical URL: set in frontmatter\n□ OG tags: og:title, og:description, og:image present\n□ Twitter Cards: twitter:card, twitter:image present\n□ URL slug: lowercase, hyphens, <60 chars\n□ Image alt text: present on all images\n\nOutput: Checklist with pass/fail per item and specific fixes.","stream":false}' \
| python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > SEO-CHECKLIST.md
Cloud fallback (--cloud or if Ollama not running):
Run these skill invocations in sequence:
3a-cloud. Use Skill tool with name="blog-geo":
Score the blog post at <file-path> for AI citation readiness across ChatGPT, Perplexity, and Google AI Overviews. Output a 0-100 score and platform-specific recommendations. Save the analysis as GEO-ANALYSIS.md in the post directory.
3b-cloud. Use Skill tool with name="seo-page":
Run a deep single-page SEO analysis on the blog post at <file-path>. Cover on-page elements, content quality, technical meta tags, schema, images, and performance. Report the overall score and critical issues.
Then use Skill tool with name="seo-technical":
Run a technical SEO audit on the blog post at <file-path>. Cover crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, JavaScript rendering, and IndexNow. Report the technical score and critical issues.
3c-cloud. Use Skill tool with name="seo-schema":
Detect and validate schema markup for the blog post at <file-path>. Generate missing JSON-LD for Article/BlogPosting, Organization, Person, and BreadcrumbList. Save to schema.json in the post directory.
3d-cloud. Use Skill tool with name="blog-seo-check":
Run the post-writing SEO validation checklist on the blog post at <file-path>. Check title tag, meta description, heading hierarchy, internal/external links, canonical URL, OG tags, Twitter Cards, URL structure, and image alt text. Report pass/fail per item with fix recommendations.
Report: Optimisation complete — GEO score: <N>/100, SEO score: <N>/100, schema generated
Step 4 — Review gate (MANDATORY)
STOP. Do not publish anything yet.
Present a full summary to the user:
═══════════════════════════════════════
KTG HUB — READY TO PUBLISH
═══════════════════════════════════════
Post: <title>
File: <path>
VARIANTS GENERATED:
✓ Medium → social-medium.md
✓ Reddit → social-reddit.md
✓ X thread → social-x-thread.md
✓ Meta → social-meta.md
✓ LinkedIn → social-linkedin.md
IMAGES:
✓ Hero 16:9 → hero-16x9.png
✓ LinkedIn crop → hero-linkedin.png
✓ X crop → hero-x.png
✓ Square crop → hero-square.png
OPTIMISATION:
✓ GEO pass → GEO-ANALYSIS.md
✓ SEO audit → SEO-ANALYSIS.md
✓ SEO checklist → SEO-CHECKLIST.md
✓ Schema → schema.json
CHANNELS:
→ Reddit r/ClaudeAI
→ LinkedIn personal feed
→ Vercel deploy (canonical URL first)
═══════════════════════════════════════
Then ask:
Review the variants before publishing. Type YES to publish to all channels, SKIP to exclude a channel, or STOP to cancel.
Do not proceed until explicit YES is received.
Step 5 — Publish
5a. Vercel deploy first (get canonical URL):
Use Composio to deploy the post to Vercel. Capture the canonical URL from the deploy response.
Substitute the canonical URL into all social variants where [CANONICAL_URL] placeholder appears.
5b. Fire each channel:
Use Composio MCP tools to publish:
| Channel | Content | Image |
|---|
| Medium | social-medium.md | none (link post) |
| Reddit r/ClaudeAI | social-reddit.md | none (link post) |
| X | social-x-thread.md | hero-x.png |
| Meta | social-meta.md | hero-square.png |
| LinkedIn | social-linkedin.md | hero-linkedin.png |
For each channel, report success or failure. If a channel fails, report the error and continue with remaining channels — do not abort the whole pipeline.
5c. Final report:
═══════════════════════════════════════
KTG HUB — PUBLISHED
═══════════════════════════════════════
✓ Vercel → <canonical-url>
✓ Medium → <post-url>
✓ Reddit → <post-url>
✓ X → <post-url>
✓ Meta → <post-url>
✓ LinkedIn → <post-url>
═══════════════════════════════════════
5d. Wiki log:
After successful publish, append to wiki/log.md:
- $(date +%Y-%m-%d) — Published: <title> → <canonical-url>
Update wiki/hot.md with the published URL and status.
Error handling
- Missing file: Report path not found, stop.
- Skill fails: Report which skill name failed, offer to retry that step only. Use the exact skill name from the Plugin Map.
- Ollama not running: Check
curl http://localhost:11434/api/tags. If fails, fall back to --cloud mode for all text tasks.
- Ollama model missing: If requested model not installed, run
ollama pull <model> or fall back to --cloud.
- Ollama context overflow: If post >8k words, chunk into summaries. Ministral context = ~32k tokens.
- ImageMagick missing: Skip crops, note in review gate, continue.
- Composio channel fails: Report error, continue other channels.
- User types STOP at gate: Cancel cleanly. All generated files are kept.
Notes
- The review gate is non-negotiable — never auto-publish.
- Local-first by default: Ollama handles text tasks (repurpose, SEO, GEO, schema). Cloud skills only for
--cloud, image gen, live data, and publishing.
- Ollama models installed:
Ministral:latest (13.5B), Qwopus:latest (9B), QwenVL:latest (8.2B), qwen3-embedding:latest (7.6B)
- Composio connections active:
medium, reddit, x, meta, linkedin, vercel
- For Windows/PowerShell: ImageMagick commands use
magick not convert
- Post variants are saved alongside the original — the wiki auto-commit hook picks them up
- Skill invocations use the
Skill tool with exact name= from the Plugin Map. Never Read skill files directly.
