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X Research

CommunityPopular
rohunvora
x-research

General-purpose X/Twitter research agent. Searches X for real-time perspectives, dev discussions, product feedback, cultural takes, breaking news, and expert opinions. Works like a web research agent but uses X as the source. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "/x-research", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to find what devs/experts/community thinks about a topic. NOT for: posting tweets or account management. Note: currently uses recent search (last 7 days). Full-archive search is available on the same pay-per-use X API plan but not yet implemented in this skill.

Overview

Publisherrohunvora
Repositoryx-research-skill
Skill namex-research
Stars
1.2K
Forks
114
Bundled files
7
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by rohunvora on GitHub. Read the source before you install it.

Installation

Install the X Research AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/rohunvora/x-research-skill.git \
  .claude/skills/x-research
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable X Research in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads X Research on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so X Research is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

X Research

General-purpose agentic research over X/Twitter. Decompose any research question into targeted searches, iteratively refine, follow threads, deep-dive linked content, and synthesize into a sourced briefing.

For X API details (endpoints, operators, response format): read references/x-api.md.

CLI Tool

All commands run from this skill directory:

bash
cd ~/clawd/skills/x-research
source ~/.config/env/global.env

Search

bash
bun run x-search.ts search "<query>" [options]

Options:

  • --sort likes|impressions|retweets|recent — sort order (default: likes)
  • --since 1h|3h|12h|1d|7d — time filter (default: last 7 days). Also accepts minutes (30m) or ISO timestamps.
  • --min-likes N — filter by minimum likes
  • --min-impressions N — filter by minimum impressions
  • --pages N — pages to fetch, 1-5 (default: 1, 100 tweets/page)
  • --limit N — max results to display (default: 15)
  • --quick — quick mode: 1 page, max 10 results, auto noise filter (-is:retweet -is:reply), 1hr cache, cost summary
  • --from <username> — shorthand for from:username in query
  • --quality — filter low-engagement tweets (≥10 likes, post-hoc)
  • --no-replies — exclude replies
  • --save — save results to ~/clawd/drafts/x-research-{slug}-{date}.md
  • --json — raw JSON output
  • --markdown — markdown output for research docs

Auto-adds -is:retweet unless query already includes it. All searches display estimated API cost.

Examples:

bash
bun run x-search.ts search "BNKR" --sort likes --limit 10
bun run x-search.ts search "from:frankdegods" --sort recent
bun run x-search.ts search "(opus 4.6 OR claude) trading" --pages 2 --save
bun run x-search.ts search "$BNKR (revenue OR fees)" --min-likes 5
bun run x-search.ts search "BNKR" --quick
bun run x-search.ts search "BNKR" --from voidcider --quick
bun run x-search.ts search "AI agents" --quality --quick

Profile

bash
bun run x-search.ts profile <username> [--count N] [--replies] [--json]

Fetches recent tweets from a specific user (excludes replies by default).

Thread

bash
bun run x-search.ts thread <tweet_id> [--pages N]

Fetches full conversation thread by root tweet ID.

Single Tweet

bash
bun run x-search.ts tweet <tweet_id> [--json]

Watchlist

bash
bun run x-search.ts watchlist                       # Show all
bun run x-search.ts watchlist add <user> [note]     # Add account
bun run x-search.ts watchlist remove <user>          # Remove account
bun run x-search.ts watchlist check                  # Check recent from all

Watchlist stored in data/watchlist.json. Use for heartbeat integration — check if key accounts posted anything important.

Cache

bash
bun run x-search.ts cache clear    # Clear all cached results

15-minute TTL. Avoids re-fetching identical queries.

Research Loop (Agentic)

When doing deep research (not just a quick search), follow this loop:

1. Decompose the Question into Queries

Turn the research question into 3-5 keyword queries using X search operators:

  • Core query: Direct keywords for the topic
  • Expert voices: from: specific known experts
  • Pain points: Keywords like (broken OR bug OR issue OR migration)
  • Positive signal: Keywords like (shipped OR love OR fast OR benchmark)
  • Links: url:github.com or url: specific domains
  • Noise reduction: -is:retweet (auto-added), add -is:reply if needed
  • Crypto spam: Add -airdrop -giveaway -whitelist if crypto topics flooding

2. Search and Extract

Run each query via CLI. After each, assess:

  • Signal or noise? Adjust operators.
  • Key voices worth searching from: specifically?
  • Threads worth following via thread command?
  • Linked resources worth deep-diving with web_fetch?

3. Follow Threads

When a tweet has high engagement or is a thread starter:

bash
bun run x-search.ts thread <tweet_id>

4. Deep-Dive Linked Content

When tweets link to GitHub repos, blog posts, or docs, fetch with web_fetch. Prioritize links that:

  • Multiple tweets reference
  • Come from high-engagement tweets
  • Point to technical resources directly relevant to the question

5. Synthesize

Group findings by theme, not by query:

### [Theme/Finding Title]

[1-2 sentence summary]

- @username: "[key quote]" (NL, NI) [Tweet](url)
- @username2: "[another perspective]" (NL, NI) [Tweet](url)

Resources shared:
- [Resource title](url) — [what it is]

6. Save

Use --save flag or save manually to ~/clawd/drafts/x-research-{topic-slug}-{YYYY-MM-DD}.md.

Refinement Heuristics

  • Too much noise? Add -is:reply, use --sort likes, narrow keywords
  • Too few results? Broaden with OR, remove restrictive operators
  • Crypto spam? Add -$ -airdrop -giveaway -whitelist
  • Expert takes only? Use from: or --min-likes 50
  • Substance over hot takes? Search with has:links

Heartbeat Integration

On heartbeat, can run watchlist check to see if key accounts posted anything notable. Flag to Frank only if genuinely interesting/actionable — don't report routine tweets.

File Structure

skills/x-research/
├── SKILL.md           (this file)
├── x-search.ts        (CLI entry point)
├── lib/
│   ├── api.ts         (X API wrapper: search, thread, profile, tweet)
│   ├── cache.ts       (file-based cache, 15min TTL)
│   └── format.ts      (Telegram + markdown formatters)
├── data/
│   ├── watchlist.json  (accounts to monitor)
│   └── cache/          (auto-managed)
└── references/
    └── x-api.md        (X API endpoint reference)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the X Research AI skill do?

General-purpose X/Twitter research agent. Searches X for real-time perspectives, dev discussions, product feedback, cultural takes, breaking news, and expert opinions. Works like a web research agent but uses X as the source. Use when: (1) user says "x research", "search x for", "search twitter for", "what are people saying about", "what's twitter saying", "check x for", "x search", "/x-research", (2) user is working on something where recent X discourse would provide useful context (new library releases, API changes, product launches, cultural events, industry drama), (3) user wants to fin...

Why use X Research on TypingMind?

Because you install it once and use it with any model. X Research is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install X Research in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rohunvora/x-research-skill/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use X Research?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with X Research?

As many as you like. As long as a model supports skills, you can use X Research with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the X Research AI skill free?

It is published on GitHub by rohunvora. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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