--- name: hub-swarm description: > KTG content marketing pipeline — SWARM MODE. Orchestrates 7 plugins via parallel agent dispatch. Drop a post, get it published everywhere with maximum parallelism. Local-first: Ollama for text, cloud for images and live data. Agents run simultaneously, not sequentially. user-invokable: true argument-hint: " [--cloud] [--ads] [--canvas]" disable-model-invocation: false metadata: author: ktg version: "2.2.0" --- # Hub-Swarm: Parallel Content Pipeline Drop a post. Spawn agents. Publish everywhere. ## Local-First Routing All text agents default to Ollama. Image + publish agents use cloud. | Swarm | Local (Ollama) | Cloud (Skill tool) | Default | |-------|---------------|-------------------|---------| | Content | `Ministral:latest` (13.5B) | `blog-repurpose` | **Local** | | SEO (5 agents) | `Qwopus:latest` (9B) | `blog-geo`, `seo-page`, etc. | **Local** | | Ads brief | `Qwopus:latest` (9B) | `ads-create` | **Local** | | Image hero | — | `blog-image` → `banana` | **Cloud** | | Image crops | ImageMagick (local binary) | — | **Local** | | Publish | — | Composio MCP | **Cloud** | **Override:** `--cloud` skips Ollama, uses Skill tool for all text tasks. ## Architecture ``` PHASE 0: VALIDATE (Sequential — fast) └─ Validate input file exists, extract title/slug └─ Check Ollama: curl http://localhost:11434/api/tags PHASE 1: SWARM DISPATCH (Parallel — all agents at once) ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ CONTENT │ │ IMAGES │ │ SEO │ │ ollama- │ │ blog-image │ │ ollama-geo │ │ repurpose │ │ or banana │ │ ollama-seo │ │ (5 agents) │ │ │ │ (5 agents) │ └─────────────┘ └─────────────┘ └─────────────┘ ┌─────────────┐ ┌─────────────┐ │ ADS │ │ CANVAS │ │ ollama-ads │ │ canvas- │ │ (optional) │ │ generate │ │ │ │ (optional) │ └─────────────┘ └─────────────┘ PHASE 2: GATHER (Sequential — collect results) └─ Wait for all agents. Assemble artifact manifest. PHASE 3: REVIEW GATE (Sequential — human checkpoint) └─ Show manifest. Wait for explicit YES per channel. PHASE 4: PUBLISH SWARM (Parallel — all channels at once) ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ VERCEL │ │ WORDPRESS │ │ SOCIAL │ │ deploy │ │ publish │ │ Reddit │ │ │ │ │ │ LinkedIn │ │ │ │ │ │ X │ └─────────────┘ └─────────────┘ └─────────────┘ ┌─────────────┐ │ ADS │ │ Google Ads │ │ Meta Ads │ │ LinkedIn │ │ TikTok │ └─────────────┘ ``` --- ## Plugin → Skill Mapping | Swarm Agent | Actual Skill Name | Scope | Invocation | |-------------|------------------|-------|------------| | `blog-repurpose` | `blog-repurpose` | User (`~/.agents/skills/`) | `Skill` tool, prompt with file path + all platforms | | `blog-image` | `blog-image` | User (`~/.agents/skills/`) | `Skill` tool, `generate ` | | `banana` | `banana` | Project (`.claude/skills/`) | `Skill` tool, `generate ` | | `blog-geo` | `blog-geo` | User (`~/.agents/skills/`) | `Skill` tool, prompt with file path | | `seo-page` | `seo-page` | User (`~/.agents/skills/`) | `Skill` tool, `` or file path | | `seo-technical` | `seo-technical` | User (`~/.agents/skills/`) | `Skill` tool, `` or file path | | `seo-schema` | `seo-schema` | User (`~/.agents/skills/`) | `Skill` tool, `` or file path | | `blog-seo-check` | `blog-seo-check` | User (`~/.agents/skills/`) | `Skill` tool, prompt with file path | | `ads-create` | `ads-create` | User (`~/.agents/skills/`) | `Skill` tool, prompt with brand + post | | `ads-generate` | `ads-generate` | User (`~/.agents/skills/`) | `Skill` tool, prompt with campaign brief | | `canvas-generate` | `canvas-generate` | Project (`.claude/skills/`) | `Skill` tool, prompt with post content | --- ## Swarm Agent Definitions ### Content Swarm **Default (local):** 5 parallel Ollama agents, one per platform. ```yaml agent: ollama-repurpose-medium model: Ministral:latest parallel: true task: > curl -s http://localhost:11434/api/generate -d '{"model":"Ministral:latest","prompt":"Write a Medium article (800-1200 words, professional tone, discussion prompt) based on this post:\n\n Output only the article.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-medium.md output: social-medium.md agent: ollama-repurpose-reddit model: Ministral:latest parallel: true task: > 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 post:\n\n Output only the post.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-reddit.md output: social-reddit.md agent: ollama-repurpose-x model: Ministral:latest parallel: true task: > curl -s http://localhost:11434/api/generate -d '{"model":"Ministral:latest","prompt":"Write an X thread (hook + 8-15 tweets, engagement CTA) based on this post:\n\n Output only the thread, one tweet per line.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-x-thread.md output: social-x-thread.md agent: ollama-repurpose-meta model: Ministral:latest parallel: true task: > curl -s http://localhost:11434/api/generate -d '{"model":"Ministral:latest","prompt":"Write a Facebook/Meta post (scannable, key takeaways, CTA) based on this post:\n\n Output only the post.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-meta.md output: social-meta.md agent: ollama-repurpose-linkedin model: Ministral:latest parallel: true task: > curl -s http://localhost:11434/api/generate -d '{"model":"Ministral:latest","prompt":"Write a LinkedIn article (professional, data-forward, 800-1200 words, discussion prompt) based on this post:\n\n Output only the article.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > social-linkedin.md output: social-linkedin.md ``` **Cloud fallback (`--cloud`):** ```yaml agent: blog-repurpose skill_name: blog-repurpose scope: user parallel: true task: > Use the Skill tool with name="blog-repurpose". Prompt: "Read the blog post at . Repurpose it for ALL platforms: Medium, Reddit, X, Meta, LinkedIn. Generate all five variants." output: social-*.md (5 files) ``` ### Image Swarm ```yaml agent: blog-image skill_name: blog-image scope: user parallel: true dependency: validate_complete task: > Use the Skill tool with name="blog-image". Prompt: "Generate a hero image for a blog post titled ''. Topic: <one-sentence summary>. Style: editorial, AI/tech theme, no text overlay. Aspect ratio: 16:9. Save to hero-16x9.png in the post directory." fallback: > If blog-image MCP unavailable, use Skill tool with name="banana". Prompt: "Generate a hero image for '<title>'. <summary>. Style: editorial, AI/tech. Aspect ratio: 16:9. Size: 2K. Save to hero-16x9.png." output: hero-16x9.png agent: image-crop skill_name: bash (ImageMagick) scope: local parallel: true dependency: hero_generated task: > Run ImageMagick crops 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 output: hero-*.png (3 files) ``` ### SEO Swarm **Default (local):** 5 parallel Ollama agents. ```yaml agent: ollama-geo model: Qwopus:latest parallel: true dependency: validate_complete task: > curl -s http://localhost:11434/api/generate -d '{"model":"Qwopus:latest","prompt":"You are a GEO analyst. Score this post for AI citation readiness (ChatGPT, Perplexity, Google AIO).\n<post-frontmatter + first 2000 words + headings>\n Rate 0-100 on: Passage Citability, Structural Readability, Authority Signals, Technical Accessibility, Freshness. Output GEO Readiness Score: XX/100 with platform breakdown and top 5 changes.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > GEO-ANALYSIS.md output: GEO-ANALYSIS.md agent: ollama-seo-page model: Qwopus:latest parallel: true dependency: validate_complete task: > curl -s http://localhost:11434/api/generate -d '{"model":"Qwopus:latest","prompt":"You are an SEO auditor. Analyze this post for on-page SEO and content quality.\n<post-frontmatter + first 2000 words + headings>\n Score 0-100 per: On-Page SEO, Content Quality, Technical Meta, Images. Output overall score with category breakdown and prioritized fixes.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > SEO-PAGE.md output: SEO-PAGE.md agent: ollama-seo-technical model: Qwopus:latest parallel: true dependency: validate_complete task: > curl -s http://localhost:11434/api/generate -d '{"model":"Qwopus:latest","prompt":"You are a technical SEO auditor. This is a static Markdown file (not a live site). Audit:\n<post-frontmatter + headings + links + image refs>\n Check: heading hierarchy, internal links (3+), external links (2+), image alt text, URL slug, canonical, OG hints, mobile readiness. Output Technical Score: XX/100 with fixes.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > SEO-TECHNICAL.md output: SEO-TECHNICAL.md agent: ollama-schema model: Ministral:latest parallel: true dependency: validate_complete task: > curl -s http://localhost:11434/api/generate -d '{"model":"Ministral:latest","prompt":"Generate valid JSON-LD schema.org for this blog post.\nFrontmatter: <frontmatter>\nTitle: <title>\nAuthor: <author>\nPublished: <date>\nModified: <date>\nURL: <canonical>\n Required: Article/BlogPosting, Organization, Person, BreadcrumbList. Output ONLY valid JSON-LD inside ```json ... ``` blocks.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > schema.json output: schema.json agent: ollama-seo-check model: Qwopus:latest parallel: true dependency: validate_complete task: > curl -s http://localhost:11434/api/generate -d '{"model":"Qwopus:latest","prompt":"Run post-writing SEO validation checklist.\n<full post>\n Check: title (40-60 chars), meta (150-160), H1 (exactly one), hierarchy (no skips), internal links (3+), external links (2+), canonical, OG, Twitter Cards, URL slug, image alt text. Output pass/fail per item with fixes.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > SEO-CHECKLIST.md output: SEO-CHECKLIST.md ``` **Cloud fallback (`--cloud`):** ```yaml agent: blog-geo skill_name: blog-geo scope: user parallel: true task: > Use Skill tool with name="blog-geo". Prompt: "Score <file-path> for AI citation readiness." output: GEO-ANALYSIS.md agent: seo-page skill_name: seo-page scope: user parallel: true task: > Use Skill tool with name="seo-page". Prompt: "Run on-page SEO analysis on <file-path>." output: SEO score card agent: seo-technical skill_name: seo-technical scope: user parallel: true task: > Use Skill tool with name="seo-technical". Prompt: "Run technical SEO audit on <file-path>." output: Technical score card agent: seo-schema skill_name: seo-schema scope: user parallel: true task: > Use Skill tool with name="seo-schema". Prompt: "Generate JSON-LD for <file-path>." output: schema.json agent: blog-seo-check skill_name: blog-seo-check scope: user parallel: true task: > Use Skill tool with name="blog-seo-check". Prompt: "Run SEO validation on <file-path>." output: Pass/fail checklist ``` ### Ads Swarm (Optional) **Default (local):** ```yaml agent: ollama-ads-create model: Qwopus:latest parallel: true condition: user_requested_ads dependency: validate_complete task: > curl -s http://localhost:11434/api/generate -d '{"model":"Qwopus:latest","prompt":"You are an ad strategist. Read this blog post and create a campaign brief.\n<post-content-or-summary>\n Output: campaign concept, messaging pillars, target audience, 3 headline options, 2 CTA options, recommended platforms. Save as campaign-brief.md.","stream":false}' | python3 -c "import sys,json; print(json.load(sys.stdin)['response'])" > campaign-brief.md output: campaign-brief.md ``` Ad creatives use cloud (`blog-image` or `banana`) — no local image gen model. **Cloud fallback (`--cloud`):** ```yaml agent: ads-create skill_name: ads-create scope: user parallel: true task: > Use Skill tool with name="ads-create". Prompt: "Read brand-profile.json and <file-path>. Produce campaign brief." output: campaign-brief.md agent: ads-generate skill_name: ads-generate scope: user parallel: true dependency: campaign-brief_complete task: > Use Skill tool with name="ads-generate". Prompt: "Read campaign-brief.md and brand-profile.json. Produce ad creatives." output: ad-creative-*.png ``` ### Canvas Swarm (Optional) ```yaml agent: canvas-generate skill_name: canvas-generate scope: project parallel: true condition: user_requested_visual_planning dependency: validate_complete task: > Use the Skill tool with name="canvas-generate". Prompt: "Create a visual canvas from the blog post at <file-path>. Detect the best archetype, generate content and visuals, instantiate template, apply layout, produce complete canvas. Save to post.canvas in post directory." output: post.canvas ``` --- ## Dependency Graph ``` validate_input ├── ollama-repurpose-* (5 agents) ──┐ │ ├──→ ollama-seo-* (5 agents, parallel) ├── blog-image/banana │ ├──→ ollama-ads-create │ │ │ └── image-crop (ImageMagick) ├───┼──→ (no dependency on ads) │ │ └───┴──→ canvas-generate (optional) ``` --- ## Review Gate Manifest ``` HUB-SWARM — READY TO PUBLISH CONTENT: Post: <title> X thread: <word_count> words LinkedIn: <word_count> words Reddit: <word_count> words Medium: <word_count> words Meta: <word_count> words IMAGES: Hero 16:9, LinkedIn crop, X crop, Square crop SEO: GEO score: <N>/100 SEO score: <N>/100 Technical score: <N>/100 Schema: <types> SEO check: <pass/fail count> ADS (if requested): Google Ads: <headline_count> headlines Meta Ads: <headline_count> headlines LinkedIn Ads: <headline_count> headlines TikTok Ads: <headline_count> headlines CANVAS (if requested): <yes/no> Visual planning CHANNELS: Vercel, WordPress, Reddit, LinkedIn, X, Meta, Medium Type YES to publish all, SKIP <channel> to exclude, STOP to cancel. ``` --- ## Performance Local Ollama runs at ~20-40 tokens/sec on RTX-class GPU. No API latency. | Phase | Sequential (cloud) | Swarm (cloud) | Swarm (local) | Speedup | |-------|-------------------|---------------|---------------|---------| | Validate | 1s | 1s | 1s (+ Ollama check) | 1x | | Content (5 variants) | 300s | 60s | 60s | 5x | | Images | 30s | 30s | 30s | 1x | | SEO (5 agents) | 225s | 45s | 45s | 5x | | Ads | 60s | 20s | 20s | 3x | | Canvas | 30s | 30s | 30s | optional | | **Total** | **~646s** | **~186s** | **~186s** | **3.5x** | **Cost:** Local = $0 in API calls. Cloud = ~$0.50-2.00 per run depending on post length. --- ## Error Handling - Agent timeout: Report which agent/skill timed out. Continue with others. - Agent failure: Report failure. Offer to retry that agent only. - Partial swarm: If 4 of 5 SEO agents succeed, use partial results. - **Ollama not running**: Check `curl http://localhost:11434/api/tags`. If fails, auto-fallback to `--cloud` mode. - **Ollama model missing**: Auto-pull with `ollama pull <model>` or fallback to `--cloud`. - **Context overflow**: If post >8k words, chunk into summaries before sending to Ollama. - Dependency failure: If blog-image/banana fails, image-crop and ads-generate skip gracefully. - ImageMagick missing: Skip crops, note in review gate, continue. --- ## Notes - **Local-first by default**: Ollama for text, cloud for images + publish - **Ollama models**: `Ministral:latest` (13.5B) for content/schema, `Qwopus:latest` (9B) for SEO/GEO/analysis - Swarm uses the `Agent` tool with `subagent_type: general` for parallel execution - Each agent gets its own context budget — no shared state - Results gathered via manifest, not conversation memory - Review gate is the only sequential bottleneck (by design) - Post-publish: wiki log entry, hot cache update - Cloud skill invocations use the `Skill` tool with exact `name=` from the Plugin Map - Never `Read` skill files directly — invoke via `Skill` tool only