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x-research

x-research

github.com/viratttProductivity27.7k41 installsUpdated 5w ago
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About x-research

x-research is a skill for researching sentiment and discussion on X/Twitter with the `x_search` tool. It structures searches, refines results, and produces a sourced briefing grouped by sentiment themes.

Key features

  1. 01Break questions into targeted searches
  2. 02Use X search operators
  3. 03Refine results to reduce noise
  4. 04Review profiles and threads
  5. 05Synthesize sourced sentiment themes

Use cases

  1. 01Assessing sentiment around a company or ticker
  2. 02Gathering bullish and bearish viewpoints
  3. 03Preparing a time-bounded briefing with cited posts

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/virattt/dexter --skill x-research

After installing, type/x-researchin Claude Code to confirm it loaded.

Details

From the project README

X Research Skill

Agentic research over X/Twitter using the x_search tool. Decompose the research question into targeted searches, iterate to refine signal, and synthesize into a sourced sentiment briefing.

Research Loop

1. Decompose into Queries

Turn the research question into 3–5 targeted queries using X operators:

  • Core query: Direct keywords or $TICKER cashtag
  • Expert voices: from:username for known analysts or accounts
  • Bearish signal: keywords like (overvalued OR bubble OR risk OR concern)
  • Bullish signal: keywords like (bullish OR upside OR catalyst OR beat)
  • News/links: add has:links to surface tweets with sources
  • Noise reduction: -is:reply to focus on original posts; -airdrop -giveaway for crypto topics
2. Execute Searches

Use the x_search tool with command: "search". For each query:

  • Start with sort: "likes" and limit: 15 to surface highest-signal tweets
  • Add min_likes: 5 or higher to filter noise for broad topics
  • Use since: "1d" or "7d" depending on how time-sensitive the topic is
  • If a query returns too much noise, narrow with more operators or raise min_likes
  • If too few results, broaden with OR terms or remove restrictive operators
3. Check Key Accounts (Optional)

For well-known analysts, fund managers, or company executives, use command: "profile" to see their recent posts directly.

4. Follow Threads (Optional)

When a high-engagement tweet appears to be a thread starter, use command: "thread" with the tweet ID to get full context.

5. Synthesize

Group findings by theme (bullish, bearish, neutral, news/catalysts):

### [Theme]

[1–2 sentence summary of the theme]

- @username: "[key quote]" — [likes]♥ [Tweet](url)
- @username2: "[another perspective]" — [likes]♥ [Tweet](url)

End with an Overall Sentiment paragraph: predominant tone (bullish/bearish/ mixed/neutral), confidence level, and any notable divergence between retail and institutional voices.

Refinement Heuristics

ProblemFix
Too much noiseRaise min_likes, add -is:reply, narrow keywords
Too few resultsBroaden with OR, remove restrictive operators
Crypto spamAdd -airdrop -giveaway -whitelist
Want expert takes onlyUse from: or min_likes: 50
Want substance over hot takesAdd has:links

Output Format

Present a structured briefing:

  1. Query Summary: what was searched and time window
  2. Sentiment Themes: grouped findings with sourced quotes and tweet links
  3. Overall Sentiment: tone, confidence, key voices
  4. Caveats: X sentiment is not a reliable predictor; sample bias toward vocal minorities; last-7-days window only

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