Facebook Research — Analyze State (v2)

Deep deconstruction of the top 5 performing videos and competitor top content.

Preconditions

• Scrape completed: .fb-research/projects/<project-name>/page-analytics.json
• Competitors scraped: .fb-research/projects/<project-name>/competitors/
• Config exists: .fb-research/projects/<project-name>/config.json

Steps

1. Load Data

cat .fb-research/projects/<project-name>/<YYYY-MM-DD_HHMMSS>/page-analytics.json  # or latest: cat .fb-research/projects/<project-name>/latest.json then session
cat .fb-research/projects/<project-name>/config.json
ls .fb-research/projects/<project-name>/competitors/

Extract: top 5 posts, page niche, your topics, competitor names.

2. For Each of the Top 5 Posts, Perform Deep Analysis

Re-navigate to each post URL:

chrome-devtools navigate_page --url "<post_url>"

Wait for full load. Extract the complete caption/description and engagement:

() => {
  const text = document.body.innerText;
  const result = {
    fullText: text.substring(0, 3000),
    ogTitle: (document.querySelector('meta[property="og:title"]') || {}).content || '',
    ogDescription: (document.querySelector('meta[property="og:description"]') || {}).content || '',
    visibleText: document.body.innerText?.substring(0, 200) || '',
  };
  return JSON.stringify(result, null, 2);
}

3. Deconstruction Framework — Analyze Each Post Against

For each of the top 5 posts, analyze these dimensions:

A. The Hook (First 3 seconds)

• Hook type: Question, bold statement, pattern interrupt, curiosity gap, statistic, controversy, story, prediction
• Hook text: The exact first line/sentence
• Hook strength: Strong / Medium / Weak — based on whether it creates an information gap
• Visual hook: What's happening on screen in the first frame (from screenshot)
• Audio hook: Music stinger, sound effect, voice tone shift, silence

B. Content Structure

• Format: Talking head, text overlay, montage, screen recording, story, tutorial, listicle, reaction
• Pacing: Fast cuts, slow build, steady, rhythmic
• Length: Short (<30s), Medium (30-60s), Long (60-120s), Extended (>120s)
• Pattern: Problem → Solution, Story → Lesson, Question → Answer, Controversy → Discussion, Tease → Reveal
• Scene breakdown: Number of distinct scenes/segments

C. Psychological Triggers Detected

D. Engagement Analysis

• Like-to-View ratio: Calculate as proxy for engagement quality
• Comment-to-View ratio: High ratio suggests strong opinion/discussion trigger
• Share-to-View ratio: High ratio suggests strong identity signaling or utility
• Comment sentiment: Positive, mixed, controversial, supportive, questioning — infer from visible comments and emoji reactions
• What drives comments: Question asked?, Controversial opinion?, Fill-in-the-blank?, Tag a friend?, Correction invitation?
• Top comment themes: What are people talking about in the top 3-5 visible comments?
• Emoji reactions breakdown: Which reactions dominate? (Like, Love, Care, HaHa, Wow, Sad, Angry)

E. Caption Analysis

• Length: Short (<50 chars), Medium (50-200), Long (200-500), Very Long (>500)
• Structure: Single line, multi-paragraph, bullet points, numbered list
• CTA: Explicit (comment/share/follow) or Implicit, Type (question, poll, tag, link, shop)
• Emoji usage: Count, placement (start/middle/end), which emojis
• Hashtags: Count, relevance (branded vs viral vs niche), placement (inline vs end)
• First line: Does it restate the hook or add new info?
• Line breaks: Short punchy lines vs dense paragraphs

F. Production Quality

• Lighting: Professional / Natural / Low / Dramatic
• Audio: Clear Voiceover / Background music / Natural sound / Mixed
• Editing: Minimal / Moderate / Heavy / Cinematic
• Text overlays: Yes/No, style (bold, animated, minimal, kinetic typography)
• Subtitles: Auto-generated / Styled captions / None — placement and style
• Color grading: Warm / Cool / Natural / High contrast / Vintage

G. Timing & Posting Pattern

• Posting time: Inferred from date text
• Day of week: Inferred from context
• Post type: Reel / Video / Live / Crosspost
• First-hour engagement: Estimated from available signals

4. Generate Analysis File

Create a markdown file with the full deconstruction for each post.

5. Analyze Competitor Top Content

For each competitor, read their scraped data:

cat .fb-research/projects/<project-name>/competitors/<competitor-name>/page-analytics.json
cat .fb-research/projects/<project-name>/competitors/<competitor-name>/raw-posts.json

Apply the same deconstruction framework (steps 2-3) to the competitor's top 3 posts. Add a comparative lens:

## Competitor: <Name>

### Page Comparison
| Metric | Our Page | Competitor | Difference |
|--------|----------|------------|------------|
| Followers | <ours> | <theirs> | +/- |
| Top Post Views | <ours> | <theirs> | +/- |
| Avg Views | <ours> | <theirs> | +/- |

### Their Top 3 Posts
For each post, run the same deconstruction framework.

### What They Do Better Than Us
- <specific advantage>
- <specific advantage>

### What We Do Better Than Them
- <specific advantage>
- <specific advantage>

### Replicable Strategies from Competitor
- <what we can copy/adapt>
- <what we can copy/adapt>

### Gaps in Their Content
- <opportunities for us>
- <opportunities for us>

6. Identify Cross-Post and Cross-Competitor Patterns

## Cross-Post Pattern Analysis

### Common Hook Types (Our Page)
- <hook type> — used in X/5 top posts

### Common Hook Types (Competitors)
- <hook type> — used across competitor top posts

### Shared Patterns (Across Our Page + Competitors)
- <pattern that everyone in the niche uses>
- <pattern that everyone in the niche uses>

### Unique Angles (Competitors have, we don't)
- <angle> — <competitor> does this, we should try it

### Unique Angles (We have, competitors don't)
- <angle> — our differentiator

### Winning Caption Formula (Across All)
- <common caption pattern>

### Optimal Posting Characteristics
- **Best length**: <duration range>
- **Best pacing**: <pacing type>
- **Best hook type**: <hook type>
- **Best CTA**: <cta pattern>
- **Best time**: <estimated time>

### Replication Blueprint
1. Start with <hook_type> hook
2. Use <format> format
3. Include <triggers> triggers
4. Structure caption as: <caption_pattern>
5. Call to action: <cta_pattern>

7. Save Analysis

cat > ".fb-research/projects/<project-name>/<YYYY-MM-DD_HHMMSS>/top5-analysis.md"  # also mirrored to project root for legacy << 'ANALYSIS_EOF'
<full analysis content>
ANALYSIS_EOF

8. Video Ideas Pipeline (skill video-idea-research)

The deep deconstruction above feeds the ideas pipeline. When the user wants video ideas for a topic, run the shared playbook with platform:facebook:

1. Top 10 by views in the window — rank the page's + competitors' top reels/videos by view count (watch pages show real view counts; fallback to engagement proxies and say so). Never invent numbers.
2. Outlines — hook (first caption line / transcript opening), beats, CTA, format, duration. Use the downloaded reels + transcribe.sh (Whisper) when the skeleton matters.
3. 5 ideas, each grounded in ≥2 top videos with their real view counts.
4. 3 scripts per idea — viral (viral_shorts), storytelling (storytelling), inspiration (motivational); TTS-ready, [HOOK]/[CTA] labels only. Optional backend seeding:

   curl -s -X POST http://localhost:8080/api/script \
     -H "Content-Type: application/json" \
     -d '{"videoSubject":"<idea title>","extraPrompt":"<angle + outline context>","aiModel":"g4f","scriptTemplate":"viral_shorts","scriptLength":"standard"}'
   

5. YouTube metadata per idea (title via the youtube-title rubric, description, tags, keywords).
6. Save video-ideas.json in the session folder and render the report:

   node "$CLAUDE_SKILL_ROOT/scripts/build-ideas-report.js" <path-to-video-ideas.json>
   # fallback: node ./skills/video-idea-research/scripts/build-ideas-report.js <path>
   

   → ideas-report.md + REPORT.html: top 10 videos + 5 ideas with scripts and metadata.

9. Report Completion

✅ Facebook Research Analysis Complete!

Project: .fb-research/projects/<project-name>/
Analysis file: top5-analysis.md

Top 5 deconstructed: ✅
Competitors analyzed: <N>
  - <competitor-1>: ✅ analyzed
  - <competitor-2>: ✅ analyzed
Cross-post patterns identified: ✅
Competitive comparison: ✅
Replication blueprint created: ✅

Key finding: <top insight about what drives success>

Next step: skill facebook-research-report