leamsigc/shortsgenerator/twitter-research

Claude Code and agent skill by leamsigc/shortsgenerator

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Twitter/X content research tool with three modes: 1. SINGLE-TOPIC MODE — explore 10+ posts across the platform based on a TOPIC the user chooses, generate scripts + audience scores + HTML report. 2. TOPICS MODE — given a broad category (e.g. "futbol mexico europa usa") and a TARGET AUDIENCE, auto-detect the top 5-10 currently-trending topics, and for each one create a standalone [topic-research].md file with: viral title, news context, media/video links, 2 TTS-ready short video scripts (virality + shock), source post + engagement stats, and an SEO-optimized YouTube title (youtube-title subskill, calibrated on the channel's own CTR/view data). Optionally hands each topic to the short-generator skill to produce a finished Short video from the collected video links + script. 3. VIDEO IDEAS MODE — research the topic on X for the video posts getting the most views inside a window (week/month/year), extract each top performer's outline, draw 5 video ideas from the top 10, and write 3 scripts per idea (viral / storytelling / inspiration) plus the YouTube metadata block (title, description, tags, keywords). Final report ranks the top 10 videos + the 5 fully-scripted ideas (shared playbook: `skill video-idea-research`). Uses X search + trending content via Chrome DevTools CLI (no API key required).

Install

npx vskill@latest install leamsigc/shortsgenerator/twitter-research

SKILL.md

Twitter/X Research — Main Skill (v3)

Two modes: Single-Topic Mode and Topics Mode.

Architecture

skills/twitter-research/ # Skill (bundled, global-installable via ~/.claude/skills/)
├── SKILL.md
└── scripts/ # Bundled — no external .twitter-research/scripts needed
├── package.json
├── scrape.js
├── report-html.js
└── report-topics-html.js
.twitter-research/ # Tool data directory (project root, auto-resolved via CWD walk-up)
└── <YYYY-MM-DD_HHMMSS>/ # One folder per research session (dated)
├── config.json
├── raw-posts.json
├── audience-scores.json
├── content-drafts.json
├── engagement-responses.json
├── REPORT.html
├── topic-research-<slug>.md # Topics mode: one per trending topic (per-session, not root)
├── topics-report.md # Topics mode index
└── screenshots/

Execution model (hybrid): heavy lifting runs as bundled scripts in skills/twitter-research/scripts/. Skills resolve dataRoot via CWD walk-up (./.twitter-research), TWITTER_RESEARCH_ROOT, or --data-root. Global-install safe (~/.claude/skills/).

Quick Start

# Single-Topic Mode (original)
/twitter-research <topic> [limit:<number>] [accounts:<account1,account2>]
# Topics Mode (NEW — research trending topics + optional Short generation)
/twitter-research topics:<category> audience:<target audience> [limit:<number>] [shorts:<on|off>]

Examples:

  • /twitter-research social media scheduling tools limit:15
  • /twitter-research topics:futbol mexico audience:aficionados liga mx shorts:on limit:10
  • /twitter-research topics:champions league audience:fans de futbol europeo

Topics Mode (NEW)

Runs the full pipeline: research → topic files → optional Short videos.

Command Parameters
ParamMeaningExample
topics:<category>Broad category/region to detect trending topics intopics:futbol mexico europa usa
audience:<text>Target audience descriptionaudience:aficionados de la liga mx
limit:<n>Max topics to research (default 5, max 10)limit:8
`shorts:<onoff>`Auto-call short-generator after research (default off)shorts:on
Workflow (state: skill twitter-research-topics)
  1. Discover trending topics — use X trending (getdaytrends.com/es/mexico or

x.com/explore) + WebSearch for the category/region. Pick the top N football (or category-relevant) topics currently hot.

  1. Research each topic — for each, pull news context, media/video links,

and real engagement stats from X search (10+ posts, real numbers).

  1. Create `[topic-research].md` files — one per topic in .twitter-research/,

containing the 6 required sections (see below).

  1. SEO YouTube titles — for each topic, load skill youtube-title and

generate the best SEO-targeted, attention-grabbing title (5 candidates scored on keyword, ALL-CAPS power word, specificity, stake, length — calibrated on the channel's own CTR/views data). Save as section 6.

  1. Optional Short generation — if shorts:on, for each topic hand off to

skill short-generator with: the viral script + the collected video links + context. Script is shown for user approval, then the video is generated and downloaded from the provided links. Uses the section 6 title for upload.

Required sections in each [topic-research].md file
  1. Title of the topic + viral title for a video
  2. Context of the topic / news (what happened, why it's hot)
  3. Video or image links related to the news
  4. 2 short video scripts — one for virality, one for shock value.

Format specifically for short vertical content, readable by a TTS (short punchy sentences, hooks, CTA).

  1. Link to the source post + engagement stats + how hot the topic is.
  2. SEO YouTube title — recommended title + 2 A/B alternates + description

keywords (via youtube-title subskill).

Output Structure (Topics Mode)
.twitter-research/<YYYY-MM-DD_HHMMSS>/
├── topic-research-<slug>.md # one per trending topic (per-session)
└── topics-report.md # summary index (per-session)
# legacy: loose topic-research-*.md at .twitter-research/ root (migrated on next run)

Video Ideas Mode

Research the topic on X video posts and produce video ideas built from the top 10 by views. Full protocol: skill video-idea-research (top-10 ranking → outline extraction → 5 ideas → viral/storytelling/inspiration scripts → YouTube metadata → REPORT.html).

/twitter-research ideas:<topic> [window:week|month|year] [limit:10] [ideas:5] [length:standard] [lang:es]

Examples:

  • /twitter-research ideas:futbol mexicano window:month
  • /twitter-research ideas:"liga mx árbitros" window:week ideas:5 length:short
X-specific research notes
StepHow (X)
Collect candidatesx.com/search?q=<topic>&f=video (+ min_faves: for quality); Latest tab for the window
Window filtersince:/until: operators (since:2026-09-10 until:2026-10-10) or keep only posts timestamped inside the window
Viewsopen the status page (/status/<id>) — the view count is on the analytics row; record real numbers only, else views: null
Ranking metricviews inside window; fallback likes + 2×retweets when views are hidden
Velocityviews / ageDays — breakouts beat big accounts
Outlinecaption text = the hook; open the video post + top replies for beats/CTA; download via short-generator when the clip matters
Outputvideo-ideas.json + ideas-report.md + REPORT.html in the session folder via node "$CLAUDE_SKILL_ROOT/scripts/build-ideas-report.js" <path> (script ships with the video-idea-research skill)

Single-Topic Mode (original v2 workflow)

Workflow
Phase 1: Setup (skill twitter-research-setup)
  1. Ask user for the research topic (e.g., "social media scheduling tools", "Liga MX")
  2. Ask for minimum posts to collect (default: 10, recommend 10-15)
  3. Ask for optional seed accounts to bootstrap the search (can be empty)
  4. Define target audience keywords and niche
  5. Set up output directory structure
  6. Ensure Chrome is configured for X/Twitter access
Phase 2: Scrape (skill twitter-research-scrape)
  1. Run the scraper: node "$CLAUDE_SKILL_ROOT/scripts/scrape.js" <timestamp> # fallback: node ./skills/twitter-research/scripts/scrape.js <timestamp>
  • Searches X by topic (Top + Latest tabs), scrolls, extracts 10+ posts from different accounts
  • Optionally visits seed accounts from config and keeps topic-relevant posts
  • Deduplicates by URL, ranks by engagement, saves raw-posts.json
  1. If search fails or returns too few results, the skill falls back to Chrome DevTools CLI for manual extraction, or broaden the query via topic keywords.
Phase 3: Analyze (skill twitter-research-analyze)
  1. Score audience segments 1-10 based on engagement data
  2. Generate social media post drafts from top content
  3. Generate video script drafts from top content
  4. Identify content patterns and angles that work on that topic
Phase 4: Report (skill twitter-research-report)
  1. Generate pre-defined engagement responses (3 per topic post)
  2. Run node "$CLAUDE_SKILL_ROOT/scripts/report-html.js" <timestamp> to generate a self-contained HTML report
  3. Include direct links to all source posts + content playbook

Output Structure

.twitter-research/
└── <YYYY-MM-DD_HHMMSS>/
├── config.json # Research parameters (topic, limits)
├── raw-posts.json # 10+ topic posts with metrics (across accounts)
├── audience-scores.json # Audience segment scores
├── content-drafts.json # Generated post & script drafts
├── engagement-responses.json # Pre-defined responses per topic post
└── REPORT.html # Self-contained final report

Key Features

FeatureDescription
Topic-based researchSearches X for a user-chosen topic, collects 10+ posts across accounts
Video ideas modeTop-10 videos by views → outlines → 5 ideas × 3 scripts + YouTube metadata (via video-idea-research)
No API keyUses Chrome DevTools CLI — works with X's web interface
Engagement responses3 pre-written responses per topic post (value add / discussion / agree)
Audience scoringScores audience segments 1-10 by engagement potential
Content generationSocial media posts + video scripts from top content
HTML reportSelf-contained, styled, with clickable post links

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
348
Repository forks
75
7-day trend score
29

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