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 "" [ 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 — 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: 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.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: bun run x-search.ts thread < tweet_id

1. 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
2. Synthesize Group findings by theme, not by query:

[Theme/Finding Title]

[1-2 sentence summary] - @username: "[key quote]" (NL, NI) Tweet - @username2: "[another perspective]" (NL, NI) Tweet Resources shared: - Resource title — [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)