x-research

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.

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Install skill "x-research" with this command: npx skills add virattt/dexter/virattt-dexter-x-research

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

  1. 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

  1. Check Key Accounts (Optional)

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

  1. 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.

  1. Synthesize

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

[Theme]

[1–2 sentence summary of the theme]

  • @username: "[key quote]" — [likes]♥ Tweet
  • @username2: "[another perspective]" — [likes]♥ Tweet

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

Problem Fix

Too much noise Raise min_likes , add -is:reply , narrow keywords

Too few results Broaden with OR , remove restrictive operators

Crypto spam Add -airdrop -giveaway -whitelist

Want expert takes only Use from: or min_likes: 50

Want substance over hot takes Add has:links

Output Format

Present a structured briefing:

  • Query Summary: what was searched and time window

  • Sentiment Themes: grouped findings with sourced quotes and tweet links

  • Overall Sentiment: tone, confidence, key voices

  • Caveats: X sentiment is not a reliable predictor; sample bias toward vocal minorities; last-7-days window only

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