# X Search > Search X/Twitter for real-time developer discourse, product feedback, community sentiment, and expert opinions. Use when user says "x search", "search x for", "search twitter for", "what are people saying about", or needs recent X discourse for context (library releases, API changes, product launches, industry discussion). Also use when researching a library, framework, API, or product to supplement web search with real-time community signal — e.g. "research Bun", "what do devs think of Hono", "is Turso production-ready". Use when this capability is needed. - Skill: `tomevault-io/x-search-2` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/x-search-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/x-search-2/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Research & Search - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/x-search-2 --- # X Search ## Priorities Signal quality > Source attribution > API cost efficiency ## Goal Surface real-time perspectives, developer discussions, product feedback, and expert opinions from X/Twitter. The value you provide is turning raw social discourse into a sourced, structured briefing — separating signal from noise and attributing every claim to its source with engagement context. ## Platform Constraints These are hard technical limits that shape your approach: - **Auth**: Requires `X_BEARER_TOKEN` env var (Basic tier, $200/mo from https://developer.x.com). - **Time window**: Basic tier covers last 7 days only — you cannot search older tweets, so don't promise historical analysis. - **Rate limits**: 450 requests per 15-minute window. The CLI adds 350ms delay between calls, but be aware during multi-page research that you're consuming a shared budget. - **Filtering**: `min_likes`/`min_retweets` search operators are unavailable on Basic tier. The CLI filters post-hoc from `public_metrics` instead — this means you still fetch the full result set even when filtering aggressively. - **Volume**: Max 100 tweets per request, max 5 pages (500 tweets per search). For most research questions this is sufficient; if not, refine queries rather than paginating blindly. ## CLI Tool Locate the CLI entry point: ``` Glob(pattern: "**/sdlc/**/utils/x-search/x-search.ts", path: "~/.claude/plugins") ``` Run via Bash tool with the resolved path. The CLI has built-in `--help` for each subcommand. Key subcommands: - **`search "" [options]`** — Search tweets. Useful options: `--sort` (likes/impressions/retweets/recent), `--since` (1h/3h/12h/1d/7d), `--min-likes N`, `--pages N` (1-5), `--limit N`, `--no-replies`, `--save`. Auto-adds `-is:retweet` unless your query already includes it. - **`profile [--count N] [--replies]`** — Recent tweets from a user (excludes replies by default). - **`thread [--pages N]`** — Full conversation thread from a root tweet. - **`tweet `** — Fetch a single tweet with full metadata. - **`watchlist [add|remove|check]`** — Manage tracked accounts (stored in `data/watchlist.json` alongside CLI). - **`cache clear`** — Clear cached results (15-minute TTL). Output defaults to markdown. Use `--json` for raw data, `--save` to write to CWD as `x-research-{slug}-{date}.md`. ## Research Approach For a quick single search, just run the query and present results. For deeper research questions, use an iterative approach: **Decompose the question into targeted searches.** Think about what angles will surface useful signal: the core topic, known expert voices (`from:` operator), pain points vs positive sentiment, and linked resources (`has:links`, `url:domain`). Use X search operators to reduce noise — the reference docs below cover the full operator set. **Iterate based on what you find.** After each search, assess: Is this signal or noise? Are there expert voices worth searching directly? High-engagement threads worth following? Linked resources worth fetching? Adjust your queries based on what the data tells you rather than running a fixed set. **Follow threads and linked content.** Threads often contain the most substantive takes because they allow nuance. When tweets link to GitHub repos, blog posts, or docs, use `web_fetch` to get the full context — especially for links that multiple tweets reference or that come from high-engagement sources. **Synthesize by theme, not by query.** Group your findings around what you learned, not how you searched. Each theme should include a brief summary, attributed quotes with engagement metrics (likes, impressions), and links to referenced resources. ## Improving Search Quality Use your judgment to adapt these strategies: - **Too much noise?** Exclude replies (`-is:reply`), sort by likes, use more specific keywords. - **Too few results?** Broaden with `OR` operators, remove restrictive filters, try alternative terminology. - **Crypto/spam flooding?** Add exclusions like `-$ -airdrop -giveaway -whitelist`. - **Want substance over hot takes?** Filter for tweets with links (`has:links`) or minimum engagement (`--min-likes`). - **Want expert perspectives?** Use `from:` for known voices in the space, or sort by engagement to surface authoritative tweets. Match your search depth to the question. A "what do people think about X?" question might need one or two searches. A "comprehensive landscape of Y" might need five searches across different angles with thread follows and link deep-dives. ## References For X API endpoint details, search operators, and response structure: - `Glob(pattern: "**/sdlc/**/skills/x-search/references/x-api.md", path: "~/.claude/plugins")` → Read result ## Arguments $ARGUMENTS --- > Converted and distributed by [TomeVault](https://tomevault.io/claim/iamladi) — claim your Tome and manage your conversions.