x-research
Searches X/Twitter for real-time discourse, developer discussions, and industry trends.
Install
mkdir -p .claude/skills/x-research && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/2537" && unzip -o skill.zip -d .claude/skills/x-research && rm skill.zipInstalls to .claude/skills/x-research
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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, account management, or historical archive searches beyond 7 days.Key capabilities
- →Search X for real-time perspectives and dev discussions
- →Filter results by engagement metrics like likes and impressions
- →Fetch full conversation threads by root tweet ID
- →Monitor specific accounts via a watchlist
- →Synthesize tweet data into markdown briefings
How it works
It decomposes research questions into targeted X search queries, fetches results via the X API, and synthesizes them into structured briefings.
Inputs & outputs
When to use x-research
- →Find developer sentiment on new libraries
- →Monitor breaking industry news
- →Gather product feedback from social discourse
About this skill
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:
cd ~/clawd/skills/x-research
source ~/.config/env/global.env
Search
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 forfrom:usernamein 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:
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
bun run x-search.ts profile <username> [--count N] [--replies] [--json]
Fetches recent tweets from a specific user (excludes replies by default).
Thread
bun run x-search.ts thread <tweet_id> [--pages N]
Fetches full conversation thread by root tweet ID.
Single Tweet
bun run x-search.ts tweet <tweet_id> [--json]
Watchlist
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
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.comorurl:specific domains - Noise reduction:
-is:retweet(auto-added), add-is:replyif needed - Crypto spam: Add
-airdrop -giveaway -whitelistif 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
threadcommand? - Linked resources worth deep-diving with
web_fetch?
3. Follow Threads
When a tweet has high engagement or is a thread starter:
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)
When not to use it
- →For historical archive searches older than 7 days
- →For managing X accounts or posting tweets
Prerequisites
Limitations
- →Limited to recent search (last 7 days)
- →Requires careful query construction to avoid noise
How it compares
It treats X as a research database rather than a social feed, using agentic loops to refine queries and extract technical insights.
Compared to similar skills
x-research side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| x-research (this skill) | 1 | 5mo | Review | Intermediate |
| web-search | 33 | 9mo | Review | Beginner |
| perplexity | 14 | 6mo | No flags | Beginner |
| perplexity-search | 13 | 7mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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