Hey community — Hector here. I want to share something I just finished building and I think a lot of you are going to find it genuinely useful — especially if you've been staring at a blank Airtable table wondering **who to add to your Content Mate X scraping list** or **what niche to actually go all-in on**. It's called **Orbix NicheFinder X**. It's free. It's one file. And it's built specifically to work hand-in-hand with Content Mate. --- ## 🤔 Here's The Problem It Solves Content Mate v2.2 is a beast. It scrapes viral content from 33+ X accounts, scores every idea, writes the scripts, generates your AI voiceover clone, creates a lipsync avatar video, adds word-by-word captions, publishes to 9 platforms, and sends you a Telegram when it's done. **All you do is open Airtable. Approve or deny.** But here's the thing — that pipeline is only as good as the X accounts you feed it. If your X table is full of random accounts you found by scrolling... your Content Mate output is going to be all over the place. Wrong niche, wrong tone, wrong audience. **NicheFinder X solves the "who do I scrape?" problem.** It finds the real players in your niche — ranked by actual follower count — so you know exactly who's dominating the space and worth modeling. --- ## 🔍 What NicheFinder X Actually Does You type in a niche keyword. You pick an industry preset. You set a minimum follower count. Hit search. It pulls back up to 100 X accounts — ranked from highest to lowest reach — with: - Their @handle - Follower / following / tweet counts - Bio excerpt - Location - Verified status - Direct link to their profile Then you download the whole thing as a **CSV** — or copy all the handles to clipboard in one click. That CSV becomes your Content Mate X account list. Done. --- ## 🚀 How to Run It (Takes About 2 Minutes) **Option 1 — Claude.ai (Easiest, No Install)** 1. Go to claude.ai 2. Upload the file: `orbix-nichefinder-x.jsx` 3. Type: *"Run this as an Artifact"* 4. It launches right in the browser

Let me paint you a picture. You're 25 minutes into a Claude Code session. You've been building a workflow, debugging a Docker issue, reading logs, fetching API docs. Things are flowing. Then the model starts forgetting what file it was editing. It asks you to repeat something you said five minutes ago. The dreaded compaction kicks in — and suddenly your AI assistant has amnesia. Sound familiar? I've been running 39,000+ deployed n8n workflows across a multi-brand portfolio. My daily work involves Docker, PostgreSQL, Traefik, Cloudflare Tunnels, Python scrapers, and a dozen other moving pieces. When I'm deep in a Claude Code session debugging a FreePBX integration or migrating Airtable bases, context window management isn't a nice-to-have — it's the difference between a productive session and starting over from scratch every 30 minutes. That's why I want to talk about **Context Mode** (https://github.com/mksglu/context-mode) — what it actually does, how it compares to working without it, and why it matters even if you're not using Claude Code. --- ## The Problem Nobody Talks About Every MCP tool call dumps raw data into your context window. Here's what that looks like in real numbers: - A **Playwright snapshot** costs 56 KB - **20 GitHub issues** cost 59 KB - **One access log** — 45 KB - A **500-row CSV** — 85 KB Your context window is 200K tokens. Sounds like a lot until you realize that with 80+ tools active, you're already burning 143K tokens (72%) before your first message even goes through. Then every tool response eats into what's left. After 30 minutes of real work, 40% of your usable context is gone. And when the agent compacts the conversation to free up space? It forgets which files it was editing, what tasks are in progress, and what you last asked for. This is the reality of working without context management. Every single one of us who uses AI coding tools has hit this wall. --- ## What Context Mode Actually Does