content-pipeline

分类: 内容与多媒体 | 上传者: claude-world | 下载: 0 | 版本: v1.0（最新）
Full-autopilot trend discovery, deep research, and social publishing pipeline. Uses trend-pulse (20 sources), cf-browser (headless Chrome), and notebooklm (research + artifacts) MCP servers. Generates algorithm-optimized content based on Meta's 7 patent-based ranking algorithms. Use when user mentions trending topics, content creation, social media publishing, trend analysis, research pipeline, viral content, content scoring, or Threads posting.
更新日志: Source: GitHub https://github.com/claude-world/claude-world-studio
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SKILL.md

---
name: content-pipeline
description: Full-autopilot trend discovery, deep research, and social publishing pipeline. Uses trend-pulse (20 sources), cf-browser (headless Chrome), and notebooklm (research + artifacts) MCP servers. Generates algorithm-optimized content based on Meta's 7 patent-based ranking algorithms. Use when user mentions trending topics, content creation, social media publishing, trend analysis, research pipeline, viral content, content scoring, or Threads posting.
user_invocable: true
---

# Content Pipeline

AI-powered content pipeline: trend discovery -> deep research -> algorithm-optimized writing -> social publishing.

## MCP Servers Required

Install via uvx (one-time, auto-cached):
```bash
uvx --from 'trend-pulse[mcp]' trend-pulse-server
uvx --from cf-browser-mcp cf-browser-mcp
uvx --from notebooklm-skill notebooklm-mcp
```

## MCP Tools Reference

### trend-pulse (12 tools)

**Trend Data:**
- **get_trending(sources, geo, count)**: Query ALL 20 free sources. sources="" for all. geo: "TW"/"US"/"JP"/"". count: 20.
  - Sources: google_trends, hackernews, mastodon, bluesky, wikipedia, github, pypi, google_news, lobsters, devto, npm, reddit, coingecko, dockerhub, stackoverflow, producthunt, arxiv, lemmy, dcard, ptt
- **search_trends(query, sources, geo)**: Cross-source keyword search.
- **list_sources()**: List all sources.
- **take_snapshot(sources, geo, count)**: Save snapshot for velocity tracking.
- **get_trend_history(keyword, days, source)**: Historical data with direction.

**Content Guide:**
- **get_content_brief(topic)**: Writing brief with hook examples, patent strategies, CTA.
- **get_scoring_guide()**: 5-dimension patent scoring. Score >= 70 required.
- **get_platform_specs(platform)**: Platform specs (char limits, algorithm signals, posting times).
- **get_review_checklist()**: Quality review checklist (7 checks).
- **get_reel_guide()**: Reels script guide (3 styles).

**Search:**
- **search_threads_posts(query)**: Search Threads posts by heat score.

### cf-browser (10 tools)

Headless Chrome via Cloudflare Browser Rendering. Use instead of WebFetch for JS-rendered pages.
- **browser_markdown(url)**: Clean Markdown. **Most used** for deep research.
- **browser_content(url)**: Full rendered HTML.
- **browser_screenshot(url)**: Full page screenshot (PNG).
- **browser_pdf(url)**: Generate PDF.
- **browser_scrape(url, selector)**: CSS selector extraction.
- **browser_json(url, schema)**: AI-driven structured data extraction.
- **browser_links(url)**: Extract all hyperlinks.
- **browser_a11y(url)**: Accessibility tree (low token cost).
- **browser_crawl(url)**: Async multi-page crawl.
- **browser_crawl_status(id)**: Check crawl progress.

### notebooklm (13 tools)

Deep research + 10 artifact types (podcast, slides, report, quiz, flashcards, mindmap, infographic, datasheet, study_guide).

**Management:** create_notebook, list_notebooks, delete_notebook
**Research:** add_source, ask, summarize, list_sources, research(mode="fast"|"thorough")
**Artifacts:** generate_artifact(type, lang?), download_artifact(type, output_path)
**Pipelines:** research_pipeline(sources, questions, output_format), trend_research(geo?, count?, platform?)

**Video Synthesis (slides + podcast -> MP4):**
1. Generate slides (PDF) + audio (podcast M4A) — sequentially
2. Download both
3. `pdftoppm -png -r 300 slides.pdf slides_page`
4. `ffmpeg -framerate 1/$per_slide -pattern_type glob -i 'slides_page-*.png' -i audio.mp3 -c:v libx264 -pix_fmt yuv420p -c:a aac -shortest output.mp4`

## Visual Content Generation

Use **NotebookLM** to generate all visual content. It produces professional-quality slides, infographics, and mind maps — far better than HTML/CSS artifacts.

### Image Cards & Slides (圖卡 / 簡報)

**Workflow:** Create a NotebookLM notebook with the content as a text source, then generate the visual artifact.

```
1. create_notebook(title="Post Visual", text_sources=["<post content + key data points>"])
2. generate_artifact(name_or_id, "slides", lang="zh-TW")   → PDF slides (best for cards)
3. download_artifact(name_or_id, "slides", "~/Downloads/card.pdf")
```

**Choose artifact type by use case:**

| Need | Artifact Type | Output |
|------|--------------|--------|
| Single image card | `slides` (1 slide) | PDF → export as image |
| Multi-slide carousel | `slides` (N slides) | PDF → split per page |
| Data visualization | `infographic` | Structured data visual |
| Topic overview | `mindmap` | Mind map diagram |
| Detailed report | `report` | Formatted document |
| Study material | `flashcards` / `study_guide` | Learning cards |

### Carousel Posts (輪播貼文)

For multi-image carousel (Threads supports 2-20 images):
1. Create notebook with content organized as numbered sections (one per slide)
2. `generate_artifact(name_or_id, "slides")` → multi-page PDF
3. Download and split: `pdftoppm -png -r 300 slides.pdf slide`
4. Each page becomes one carousel image
5. Publish with `carousel_urls`

### Video (影片)

Combine slides + podcast audio into MP4:
1. `generate_artifact(name_or_id, "slides")` → PDF
2. `generate_artifact(name_or_id, "podcast")` → M4A audio (run sequentially, NOT parallel)
3. Download both artifacts
4. `pdftoppm -png -r 300 slides.pdf slides_page`
5. `ffmpeg -framerate 1/$per_slide -pattern_type glob -i 'slides_page-*.png' -i audio.mp3 -c:v libx264 -pix_fmt yuv420p -c:a aac -shortest output.mp4`

### Tips for Better Visuals

- **Language**: Always pass `lang="zh-TW"` for Traditional Chinese content
- **Rich text sources**: The more context you feed into the notebook, the better the visual output
- **One topic per notebook**: Don't mix unrelated topics — create separate notebooks
- **Add URLs as sources**: `add_source(name_or_id, url="...")` for reference material — NotebookLM will incorporate key data into visuals

## Mandatory Rules

### 1. Read Original Sources
NEVER write content based on titles/metadata alone.
- Single topic: read >= 1 primary source via browser_markdown(url)
- Controversial: read >= 2 sources (both sides)
- Data claims: find original data source

### 2. Timeline Verification
Every fact must have a verified timestamp. Discard anything > 48 hours old.

| Source age | Allowed | Forbidden |
|---|---|---|
| Today | "today" "just now" | - |
| 1-3 days | "recently" "the other day" | "just" "latest" |
| 4-7 days | "last week" "this week" | "just" "yesterday" |
| 8-30 days | "this month" | "last week" "just" |
| >30 days | "earlier" "this year" | any freshness words |

### 3. Use ALL Sources
get_trending with sources="" to query ALL 20 sources. Do NOT filter unless user explicitly asks.

## Meta Patent-Based Scoring (5 Dimensions)

| # | Dimension | Weight | Check |
|---|-----------|--------|-------|
| 1 | Hook Power | 25% | First line: number or contrast, 10-45 chars |
| 2 | Engagement Trigger | 25% | CTA anyone can answer, direct "you" address |
| 3 | Conversation Durability | 20% | Has contrast/both sides, creates discussion |
| 4 | Velocity Potential | 15% | Timely, 50-300 chars, urgency language |
| 5 | Format Score | 15% | Mobile-scannable, line breaks, no text walls |

**Quality Gates (ALL must pass before publishing):**
- Overall Score >= 70
- Conversation Durability >= 55
- Hook: 10-45 chars with number or contrast
- CTA: clear question or poll
- Timeline: all time words verified
- Source: every claim traceable
- No AI filler words

## Pipeline Workflow

1. **Discover**: get_trending(sources="", geo, count=20)
2. **Read Source**: browser_markdown(url) — MANDATORY
3. **Verify Timeline**: Check dates, discard stale
4. **Research**: browser_markdown + WebSearch, 2-3 sources min
5. **Brief**: get_content_brief(topic)
6. **Create**: Write -> patent check (5 dimensions)
7. **Score**: get_scoring_guide — self-score (>= 70)
8. **Review**: get_review_checklist — final check
9. **NotebookLM** (optional): create notebook -> generate artifacts
10. **Publish**: provide ready-to-post content or use publish tool
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