Twitter/X Research — Topics Mode (v1)

Detects the top trending topics in a category, creates [topic-research].md files, and optionally generates Shorts.

Command

/twitter-research topics:<category> audience:<target audience> [limit:<n>] [shorts:<on|off>]

Examples:

• /twitter-research topics:futbol mexico audience:aficionados liga mx shorts:on limit:10
• /twitter-research topics:champions league audience:fans europeos limit:5

Preconditions

• Chrome is running with --remote-debugging-port=9222
• User is logged into X/Twitter in Chrome
• Backend running for short generation (only if shorts:on):

  curl -s -o /dev/null -w "%{http_code}" http://localhost:8080/api/models
  

Workflow

Step 1 — Discover Trending Topics

Find what is actually trending right now in the target category/region.

1. X trending data (country-specific):

   chrome-devtools navigate_page --url "https://getdaytrends.com/es/mexico/"
   

   Extract the current trend list via evaluate_script. Filter to topics relevant to the category (for futbol: team names, player names, tournament names, transfers, results, goals, referees).
2. X Explore for global/sports trends:

   chrome-devtools navigate_page --url "https://x.com/explore"
   

   Read the Sports / Entertainment / News trend tabs.
3. WebSearch the category + region for today's news:
   • WebSearch("<category> <region> noticias hoy")
   • WebSearch("<category> trending <region> hoy")
   • For futbol: WebSearch("futbol liga mx hoy"), WebSearch("champions league hoy"), WebSearch("mls noticias hoy")
4. Curate the top N topics (default 5, max 10). Choose topics that are:
   • Currently hot (trending in the last 24-48h)
   • Category-relevant
   • Distinct (no duplicates)
   • Video-friendly (visual content available)

Step 2 — Research Each Topic

For each of the top N topics:

1. Get news context via WebSearch: WebSearch("<topic> noticias") and read the top 2-3 results. Capture: what happened, why it matters, key numbers, reactions, official statements.
2. Search X for engagement data:

   chrome-devtools navigate_page --url "https://x.com/search?q=<URL_ENCODED_TOPIC>&src=typed_query&f=top"
   

   Wait 5s, then extract the top 5 posts with real metrics using the scrape extractor (handle, tweet text, status URL, and the numeric bar = replies / retweets / likes / views). Record the single best-performing post URL + its exact stats.
3. Collect media/video links: from the tweet media, news articles, or a quick platform search (WebSearch("site:youtube.com <topic>"), WebSearch("site:tiktok.com <topic>")). Gather 3-5 usable links.

Step 3 — Create [topic-research].md Files

For each topic, create a file named ```` .twitter-research/<YYYY-MM-DD_HHMMSS>/ ├── topic-research-.md # one per trending topic (per-session) └── topics-report.md

`.twitter-research/` (or the configured output dir). The file MUST contain
these 5 sections (in this order):

```markdown
# Topic Research: <Topic Name>
**Fecha de investigación:** <YYYY-MM-DD>
**Nivel de calor (hotness):** 🔥-🔥🔥🔥🔥🔥

## 1. Título del tema y título viral
**Tema:** <short summary of the topic>
**Títulos virales para video:**
- <viral title 1>
- <viral title 2>

## 2. Contexto de la noticia
<2-4 paragraphs: what happened, why it's hot, key facts, reactions>

## 3. Enlaces de video e imágenes
- <link with description>
- <link with description>

## 4. Guiones de video corto

### Guion A — VIRALIDAD
> [HOOK 0-3s] <hook sentence>
> <4-8 more short TTS-read sentences, one per line>
> [CTA] <call to action>

### Guion B — SHOCK VALUE
> [HOOK] <hook>
> <short punchy lines for TTS>
> <closing line>

## 5. Publicación de referencia + interacción
**Post principal:** <url>
- Respuestas: X | Reposts: X | Me gusta: X | Reproducciones: X
**¿Qué tan caliente está?** <hotness rating + note>
```

**Script writing rules (for TTS / short vertical video):**
- Spanish (or the user's language), spoken-style, no complex punctuation
- Short sentences (6-12 words), one idea per line
- Hook in first 3 seconds (question, bold claim, or shock stat)
- Rhythmic pacing; numbers written out naturally
- End with a CTA (comment / save / follow)
- NO stage directions inside the read text — use `[HOOK]`, `[CTA]` markers
  only as labels; the text after them is what the TTS reads

### Step 4 — Write `topics-report.md`

Create an index file listing all topics, their hotness, and file links:

```markdown
# Topics Report — <category>
**Fecha:** <date>
**Audiencia objetivo:** <audience>

| # | Tema | Calor | Archivo |
|---|------|-------|---------|
| 1 | ... | 🔥🔥🔥 | ```
.twitter-research/<YYYY-MM-DD_HHMMSS>/
  ├── topic-research-<slug>.md        # one per trending topic (per-session)
  └── topics-report.md
``` |
```

### Step 5 — Optional: Generate Shorts (`shorts:on`)

For each topic, hand off to the short-generator skill:

1. Load it: `skill short-generator`
2. Subject = the topic; script = the **Virality** guion from the topic file
3. Provide `hashtags:` from the topic keywords and `sources:` (default
   instagram,facebook,tiktok,youtube)
4. Collect the video links from section 3 of the topic file and use them in
   short-generator Step 4/5 (fallback sources if search finds <5 URLs)
5. **Show the generated script for user approval before generating** the video
6. On approval, generate the Short and download the videos from the links

**Important**: Always show the script and get explicit user approval before
calling the final video generation endpoint.

### Step 6 — Report Completion

```
✅ Twitter/X Research Topics Mode Complete!

Category: <category>
Audience: <audience>
Topics researched: <N>
  - <topic 1> (🔥hotness) → .twitter-research/```
.twitter-research/<YYYY-MM-DD_HHMMSS>/
  ├── topic-research-<slug>.md        # one per trending topic (per-session)
  └── topics-report.md
```
  - ...
Shorts generated: <M/N>

Next step (optional): skill twitter-research-report for a full HTML report
```