Twitter/X Research — Analyze State (v3)

Scores audiences, generates content drafts, and identifies winning patterns. The output files are consumed by twitter-research-report (node "$CLAUDE_SKILL_ROOT/scripts/report-html.js" <timestamp>).

Preconditions

• Scrape completed: .twitter-research/<YYYY-MM-DD_HHMMSS>/raw-posts.json
• Config exists: .twitter-research/<timestamp>/config.json

Steps

1. Load data

node -e "const d=require('./.twitter-research/<YYYY-MM-DD_HHMMSS>/raw-posts.json'); console.log(JSON.stringify({topic:d.topic, distinctAccounts:d.distinctAccounts, posts:d.posts.map(p=>({handle:p.handle, likes:p.likes, retweets:p.retweets, url:p.url, text:p.text.substring(0,120)}))},null,2))"

2. Audience segmentation & scoring

For each targetAudienceKeyword in config, score 1-10 using: relevance, engagement rate, content affinity, monetization potential, competition level (lower = better). Find matching posts per segment and note pain points + content angles.

Save to audience-scores.json:

{
  "analysisTimestamp": "<YYYY-MM-DD HH:MM:SS>",
  "segments": [
    {
      "segment": "social media manager",
      "finalScore": 9,
      "breakdown": {"relevance": 10, "engagementRate": 9, "contentAffinity": 8, "monetization": 9, "competitionLevel": 7},
      "verdict": "✅ Best Prospect",
      "painPoints": ["..."],
      "contentAngles": ["..."],
      "whyScore": "...",
      "matchingTweetsCount": 8
    }
  ],
  "contentPatterns": {"topHookTypes": [], "bestFormats": [], "contentCalendar": {}},
  "totalPostsAnalyzed": 10,
  "distinctAccountsAnalyzed": 7,
  "topic": "<topic>"
}

3. Generate social media post drafts

For the top topic posts, adapt each winning angle to the user's brand voice (headline, body, CTA, hashtags, best time). Generate via the backend API if available:

curl -s -X POST http://localhost:8080/api/script \
  -H "Content-Type: application/json" \
  -d '{"videoSubject":"<topic>","extraPrompt":"<build a viral social post adapting the top tweet>","aiModel":"g4f","scriptTemplate":"viral_shorts"}'

If the API is unavailable, write drafts manually based on each tweet's structure and angle.

4. Generate video script drafts

If contentFormat includes video, generate 30-60s scripts: hook → problem → solution → social proof → CTA.

5. Save to content-drafts.json

{
  "generatedAt": "<YYYY-MM-DD HH:MM:SS>",
  "postDrafts": [{"rank": 1, "sourceHandle": "@h", "sourceUrl": "...", "targetSegment": "...", "headline": "...", "body": "...", "cta": "...", "hashtags": ["#a"], "format": "social_post"}],
  "videoScripts": [{"rank": 1, "sourceHandle": "@h", "sourceUrl": "...", "targetSegment": "...", "hook": "...", "body": "...", "cta": "...", "format": "video_script"}]
}

Report Completion

✅ Twitter/X Research Analysis Complete!
Session: .twitter-research/<timestamp>/
Audience segments scored: <N> (top: <segment> <score>/10)
Content drafts: <N> posts · <N> scripts
Next step: skill twitter-research-report