diff --git a/readme.md b/readme.md
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--- a/readme.md
+++ b/readme.md
@@ -1,72 +1,60 @@
-# nCore Leaderboard Scraper (Turbo-Go 1.26+)
+# ncore-leaderboard
 
-A hyper-performance, zero-allocation Go scraper designed to saturate a Gigabit connection while extracting user ranks from ~1.8M nCore profiles in under 10 minutes.
+This is a utility for scraping user ranks from nCore profiles and storing
+the results in a SQLite database for sorting and analysis. It is designed
+for efficient data collection using concurrent workers and low-level
+parsing.
 
-## 🚀 Performance Specs
+## Requirements
 
-- **Throughput:** 5,000+ Requests Per Second (RPS) on a 1Gbps line.
-- **CPU Efficiency:** Multi-threaded worker pool utilizing all available cores with `GOMAXPROCS`.
-- **Zero-Allocation Parsing:** Raw-byte signature scanning instead of heavy DOM parsing (100x faster than `goquery`).
-- **Network Stack:** Powered by `fasthttp` for maximum connection reuse and zero-allocation networking.
-- **Storage:** Instant O(log N) lookups via **SQLite 3** with WAL-mode transactions and indexed ranks.
+- Go 1.26 or later
+- just (optional, for automated builds)
+- sqlite3 (optional, for CLI queries)
 
-## 🛠️ Features
+## Installation
 
-- **Universal Parser:** Targeted signature scanning (`profil_jobb_elso2`) ensuring 100% accuracy.
-- **Real-Time Telemetry:** Live CLI status bar with Progress, RPS, Found count, and ETA.
-- **Robust Networking:** Automated 3-stage exponential backoff retries for transient errors.
-- **Security Monitoring:** Active detection of session expiration or rate-limiting (Login page detection).
-- **Dual-Mode Output:** Sorted results saved to a professional-grade `leaderboard.db`.
+Clone the repository and install the necessary Go modules:
 
-## 📦 Requirements
+    git clone https://github.com/skidoodle/ncore-leaderboard
+    cd ncore-leaderboard
+    go mod tidy
 
-- **Go 1.26+** (Uses modern `slices`, `cmp`, and `atomic` types).
-- **Just** (Case-sensitive command runner).
-- **AVX2-capable CPU** (Targeted via `GOAMD64=v3` build flags).
+## Usage
 
-## 📥 Setup
+Create a `.env` file in the project root with your credentials:
 
-1. Clone and install dependencies:
-   ```powershell
-   git clone https://github.com/skidoodle/ncore-leaderboard
-   cd ncore-leaderboard
-   just tidy
-   ```
+    NICK=username
+    PASS=cookie_pass
 
-2. Configure your credentials in `.env.local` or `.env`:
-   ```env
-   NICK=your_username
-   PASS=your_pass_cookie_value
-   ```
+Build and execute the program using the provided justfile:
 
-## 🎮 Usage
+    just run
 
-### Build & Run
-```powershell
-just run
-```
+Alternatively, build the binary manually:
 
-### Build Only (Optimized)
-Produces a stripped, architecture-targeted `ncore-leaderboard.exe`.
-```powershell
-just build
-```
+    go build -o ncore-leaderboard main.go
+    ./ncore-leaderboard
 
-### Data Exploration
-Once scraping is complete, the results are in `leaderboard.db`. You can query it instantly:
-```powershell
-# Show top 25 users
-just top 25
+The program processes the profile range defined in `main.go` and produces
+a `leaderboard.db` file.
 
-# Query a specific rank
-just query 1066
-```
+## Data Analysis
 
-## 🏗️ Architecture details
+The results are stored in a SQLite database with indices on rank and ID.
+You can query the data using any standard SQLite client or the following
+commands:
 
-- **Concurrency:** Managed by a buffered job channel and 1,000+ goroutine workers.
-- **Memory:** Results are stored in-memory using `uint32` to halve RAM footprint before being flushed to SQLite in a single atomic transaction.
-- **Indexing:** Ranks and Profile IDs are indexed on disk for sub-millisecond leaderboard queries.
+    just top 10        # List the top 10 users by rank
+    just query 1066    # Find the user at a specific rank
 
-## ⚖️ License
-GPL-3.0 License. Built for performance, speed, and precision.
+## Implementation Details
+
+The scraper utilizes a worker pool to manage concurrent HTTP requests via
+fasthttp. It performs raw byte signature scanning on HTML responses to 
+extract data without the overhead of a DOM parser. Results are committed 
+to SQLite in a single transaction to ensure atomicity and speed.
+
+## License
+
+This software is released under the GNU General Public License v3.0.
+See the license file for details.