diff --git a/CHANGELOG.md b/CHANGELOG.md
index c31e70e6..2d74fe0b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -13,6 +13,17 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   to `1`; every Node constructor now propagates the core's validation error
   (e.g. `period must be greater than zero`), matching the Python and WASM
   bindings and the Rust core. Constructing with a valid period is unaffected.
+- **Binding package READMEs are now per-ecosystem.** The Python, Node.js, and
+  WebAssembly READMEs were byte-identical 314-line copies of the workspace
+  README and had drifted out of sync (stale indicator count, Python snippets
+  shown on the Node and WASM package pages). Each is now a focused landing page
+  with the correct install command, a language-correct quick-start snippet, and
+  links to the canonical documentation — removing the manual three-way sync
+  burden. No code or API changes.
+- **CONTRIBUTING now states the correct MSRV (1.86 workspace / 1.88
+  `bindings/node`)** and documents that these are the dependency-forced floors,
+  kept minimal on purpose. The previous text claimed 1.75 / 1.77, which the
+  `msrv` CI job has enforced against since the criterion and napi-build bumps.
 
 ## [0.3.1] - 2026-05-30
 
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 0024d09c..fec21b3c 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -35,8 +35,13 @@ cargo test --workspace
 cargo test -p wickra-data --features live-binance
 ```
 
-The minimum supported Rust version is **1.75** for the workspace crates and
-**1.77** for `bindings/node`; the `msrv` CI job enforces both.
+The minimum supported Rust version is **1.86** for the workspace crates and
+**1.88** for `bindings/node`; the `msrv` CI job enforces both. These floors are
+not chosen freely — they are the lowest versions our dependencies allow
+(criterion 0.8.2, the bench dev-dependency, requires 1.86; napi-build 2.3.2
+requires 1.88). We keep the MSRV at that dependency-forced floor on purpose so
+the library builds for the widest possible audience; please don't raise it
+without a dependency that actually requires it.
 
 ### Python
 
diff --git a/bindings/node/README.md b/bindings/node/README.md
index 1450b719..709f60e6 100644
--- a/bindings/node/README.md
+++ b/bindings/node/README.md
@@ -1,314 +1,73 @@
-# Wickra
+# Wickra — Node.js
 
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
-[![crates.io](https://img.shields.io/crates/v/wickra.svg?logo=rust&color=orange)](https://crates.io/crates/wickra)
-[![PyPI](https://img.shields.io/pypi/v/wickra.svg?logo=pypi&color=blue)](https://pypi.org/project/wickra/)
 [![npm](https://img.shields.io/npm/v/wickra.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](LICENSE)
+[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
 
-**Streaming-first technical indicators. Install with `pip install wickra` — no system dependencies.**
+**Streaming-first technical indicators for Node.js. `npm install wickra` —
+prebuilt native binary, no system dependencies.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is a state
-machine that updates in O(1) per new data point, so live trading bots and
-historical backtests share the exact same implementation.
+bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1)
+streaming state machine, so live trading bots and historical backtests share
+the exact same implementation. This package is the Node.js binding (napi-rs);
+it exposes 200+ streaming-first indicators across sixteen families.
 
-```python
-import numpy as np
-import wickra as ta
-
-# Batch: classic TA-Lib-style usage
-prices = np.linspace(100, 200, 1000)
-rsi = ta.RSI(14)
-values = rsi.batch(prices)              # numpy array, NaN during warmup
-
-# Streaming: same indicator, fed tick by tick
-rsi = ta.RSI(14)
-for price in live_feed:
-    value = rsi.update(price)           # O(1) — no recomputation over history
-    if value is not None and value > 70:
-        print("overbought")
-```
-
-## Why Wickra exists
-
-The Python TA ecosystem has plenty of libraries — TA-Lib, pandas-ta, finta,
-talipp, tulipy — and every one of them shares the same blind spot:
-
-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★ Wickra**      | **clean**       | **yes**   | **Python + Node + WASM + Rust** | **yes** |
-| TA-Lib (Python)        | yes (C deps)    | no        | no             | barely |
-| pandas-ta              | clean           | no        | no             | slow   |
-| finta                  | clean           | no        | no             | stale  |
-| ta-lib-python          | yes (C deps)    | no        | no             | barely |
-| talipp                 | clean           | yes       | no             | yes    |
-| Tulip Indicators       | yes (C deps)    | no        | partial        | stale  |
-| ooples (C#)            | clean           | no        | C# only        | yes    |
-
-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
-
-## Benchmark: how much faster is "streaming-first"?
-
-The numbers below were measured on a single developer workstation and are not
-guaranteed to reproduce identically on different hardware — absolute µs values
-depend on CPU, memory clock and OS scheduler. Read them as **relative
-speedups** between libraries on identical input, not as a universal
-performance contract.
-
-- **Reproduced on:** Windows 11 Pro 26200, AMD Ryzen 9 9950X, 64 GB DDR5,
-  Rust 1.92 (release profile, `lto = "fat"`, `codegen-units = 1`),
-  Python 3.12, Node 20.
-- **Reproduce yourself:** `pip install -e bindings/python[bench]` then
-  `python -m benchmarks.compare_libraries`. The script auto-detects every
-  installed peer library and runs them on the same generated inputs as
-  Wickra. The CI job `cross-library-bench` runs the same script on every
-  push and uploads the raw report as a build artefact.
-
-Lower µs/op = faster. Wickra wins every batch category outright, and the
-streaming gap widens linearly with how much history a batch-only library has
-to recompute on every tick.
-
-### Batch — single full pass over a 20 000-bar series
-
-Reading the table: each cell shows that library's runtime, plus how many times
-slower it is than Wickra in parentheses. **★** marks the winner per row.
-
-| Indicator           | **★ Wickra**   | finta                       | talipp                        |
-|---------------------|---------------------|-----------------------------|-------------------------------|
-| SMA(20)             | **95.6 µs ★**       | 343.5 µs (3.6× slower)      | 7 640.6 µs (79.9× slower)     |
-| EMA(20)             | **64.6 µs ★**       | 223.1 µs (3.5× slower)      | 12 160.9 µs (188.2× slower)   |
-| RSI(14)             | **126.2 µs ★**      | 1 107.1 µs (8.8× slower)    | 15 792.2 µs (125.1× slower)   |
-| MACD(12, 26, 9)     | **119.0 µs ★**      | 531.8 µs (4.5× slower)      | 49 788.1 µs (418.2× slower)   |
-| Bollinger(20, 2.0)  | **105.3 µs ★**      | 812.0 µs (7.7× slower)      | 130 938.3 µs (1 243.7× slower)|
-| ATR(14)             | **123.5 µs ★**      | 5 144.8 µs (41.7× slower)   | 28 816.0 µs (233.4× slower)   |
-
-### Streaming — per-tick latency after seeding with 5 000 historical bars
-
-A batch-only library has to re-run its full indicator over the entire history on
-every new tick; Wickra updates state in O(1).
-
-| Indicator | **★ Wickra (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
-
-> TA-Lib and pandas-ta are not included here because both fail to install
-> cleanly on Windows without C build tooling — which is precisely the install
-> pain Wickra was built to remove. The benchmark script auto-detects every
-> peer library it can find and runs them on the same inputs as Wickra; install
-> them in your environment to see those rows light up too.
-
-Run the suite yourself:
+## Install
 
 ```bash
-pip install -e bindings/python[bench]
-python -m benchmarks.compare_libraries
+npm install wickra
 ```
 
-## Indicators
+The native addon ships as a prebuilt binary per platform (Linux, macOS,
+Windows — x64 and arm64), selected automatically through optional
+dependencies. There is nothing to compile.
 
-214 streaming-first indicators across sixteen families. Every one passes the
-`batch == streaming` equivalence test, reference-value tests, and reset
-semantics tests.
+## Quick start
 
-| Family | Indicators |
-|--------|-----------|
-| Moving Averages      | SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA, ALMA, McGinley Dynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA |
-| Momentum Oscillators | RSI (Wilder), Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator, RVI, PGO, KST, SMI, Laguerre RSI, Connors RSI, Inertia |
-| Trend & Directional  | MACD, ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter |
-| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC |
-| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility, Detrended StdDev |
-| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands |
-| Trailing Stops       | Parabolic SAR, SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop |
-| Volume               | OBV, VWAP (cumulative + rolling), ADL, Volume-Price Trend, Chaikin Money Flow, Chaikin Oscillator, Force Index, Ease of Movement, Klinger Volume Oscillator, Volume Oscillator, NVI, PVI, Williams A/D, Anchored VWAP, Demand Index, TSV, VZO, Market Facilitation Index |
-| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Spearman Correlation |
-| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline |
-| Pivots & S/R         | Classic Pivots, Fibonacci Pivots, Camarilla, Woodie Pivots, DeMark Pivots, Williams Fractals, ZigZag |
-| DeMark               | TD Setup, TD Sequential, TD DeMarker, TD REI, TD Pressure, TD Combo, TD Countdown, TD Lines, TD Range Projection, TD Differential, TD Open, TD Risk Level |
-| Ichimoku & Charts    | Ichimoku Kinko Hyo (Tenkan, Kijun, Senkou A/B, Chikou), Heikin-Ashi |
-| Candlestick Patterns | Doji, Hammer, Inverted Hammer, Hanging Man, Shooting Star, Engulfing, Harami, Morning/Evening Star, Three White Soldiers/Black Crows, Piercing Line/Dark Cloud Cover, Marubozu, Tweezer, Spinning Top, Three Inside Up/Down, Three Outside Up/Down |
-| Market Profile       | Value Area (POC / VAH / VAL), Initial Balance, Opening Range |
-| Risk / Performance   | Sharpe Ratio, Sortino Ratio, Calmar Ratio, Omega Ratio, Max Drawdown, Average Drawdown, Drawdown Duration, Pain Index, Value at Risk, Conditional Value at Risk (CVaR), Profit Factor, Gain/Loss Ratio, Recovery Factor, Kelly Criterion, Treynor Ratio, Information Ratio, Alpha (Jensen) |
+```js
+const wickra = require('wickra');
 
-Adding a new indicator means implementing one trait in Rust; all four bindings
-inherit it automatically.
+// Batch: run an indicator over a whole array.
+const prices = Array.from({ length: 1000 }, (_, i) => 100 + i * 0.1);
+const values = new wickra.RSI(14).batch(prices); // null during warmup
 
-## Languages
-
-| Binding           | Install                                       | Example |
-|-------------------|-----------------------------------------------|---------|
-| Python (PyO3)     | `pip install wickra`                          | `examples/python/backtest.py` |
-| Node.js (napi-rs) | `npm install wickra`                          | `examples/node/backtest.js` |
-| Browser / WASM    | `npm install wickra-wasm`                     | `examples/wasm/index.html` |
-| Rust              | `cargo add wickra`                            | `examples/rust/src/bin/backtest.rs` |
-
-Each binding ships several runnable examples (streaming, backtest, live feed);
-[`examples/README.md`](examples/README.md) is the full cross-language index.
-
-The wickra-core crate is `unsafe`-forbidden, so every binding inherits a
-memory-safe implementation.
-
-## Rust API
-
-```rust
-use wickra::{Indicator, BatchExt, Chain, Ema, Rsi, Sma};
-
-// Streaming or batch — same trait, same code.
-let mut sma = Sma::new(14)?;
-let out: Vec<Option<f64>> = sma.batch(&[1.0, 2.0, 3.0, 4.0, 5.0]);
-
-let mut rsi = Rsi::new(14)?;
-for price in live_feed {
-    if let Some(v) = rsi.update(price) {
-        println!("RSI = {v}");
-    }
-}
-
-// Compose indicators: RSI(7) on top of EMA(14).
-let mut chain = Chain::new(Ema::new(14)?, Rsi::new(7)?);
-chain.update(price);
-```
-
-## Live data sources
-
-`wickra-data` (separate crate, opt-in) ships:
-
-- A streaming OHLCV **CSV reader**.
-- A **tick-to-candle aggregator** with arbitrary timeframes.
-- A **candle resampler** for multi-timeframe analysis (1m → 5m → 1h on the fly).
-- A **Binance Spot WebSocket** kline adapter (feature `live-binance`).
-
-```rust
-use wickra::{Indicator, Rsi};
-use wickra_data::live::binance::{BinanceKlineStream, Interval};
-
-let mut stream = BinanceKlineStream::connect(&["BTCUSDT".into()], Interval::OneMinute).await?;
-let mut rsi = Rsi::new(14)?;
-while let Some(event) = stream.next_event().await? {
-    if event.is_closed {
-        if let Some(v) = rsi.update(event.candle.close) {
-            println!("RSI = {v:.2}");
-        }
-    }
+// Streaming: the same indicator, fed tick by tick in O(1).
+const rsi = new wickra.RSI(14);
+for (const price of liveFeed) {
+  const value = rsi.update(price); // no recomputation over history
+  if (value !== null && value > 70) {
+    console.log('overbought');
+  }
 }
 ```
 
-A Python live-trading example using the public `websockets` package lives at
-`examples/python/live_trading.py`.
+`batch(prices)` and feeding the same prices through `update()` produce
+identical values — the equivalence is enforced by the test suite.
 
-## Project layout
+## Documentation
 
-```
-wickra/
-├── crates/
-│   ├── wickra-core/         core engine + all 71 indicators
-│   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
-├── bindings/
-│   ├── python/              PyO3 + maturin (publishes on PyPI)
-│   ├── node/                napi-rs (publishes on npm)
-│   └── wasm/                wasm-bindgen (browsers, bundlers, Node)
-├── examples/                examples/README.md indexes every language
-│   ├── data/                real BTCUSDT OHLCV datasets, one per timeframe
-│   ├── rust/                Rust workspace member (`wickra-examples`)
-│   ├── python/              backtest, live trading, parallel assets, multi-tf
-│   ├── node/                streaming, backtest, live trading (load `wickra`)
-│   └── wasm/                browser demo for `wickra-wasm`
-└── .github/workflows/       CI and release pipelines
-```
+The full indicator catalogue, guides, quickstarts, and API reference live in
+the main repository and wiki:
 
-Rust benchmarks live in `crates/wickra/benches/`; runnable Rust examples live
-in the workspace member crate at `examples/rust/`. There is no top-level
-`benches/` directory.
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Wiki** (quickstarts, cookbook, TA-Lib migration): <https://github.com/wickra-lib/wickra/wiki>
+- **Runnable examples:** [`examples/node/`](https://github.com/wickra-lib/wickra/tree/main/examples/node)
 
-## Building everything from source
+Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
+expose the same indicators from the shared, `unsafe`-forbidden Rust core.
 
-```bash
-# Rust core + tests
-cargo test --workspace
-cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
+## Disclaimer
 
-# Python binding (requires Rust toolchain + maturin)
-cd bindings/python
-maturin develop --release
-pytest
-
-# WASM binding (requires wasm-pack + wasm32-unknown-unknown target)
-wasm-pack build bindings/wasm --target web --release --features panic-hook
-
-# Node binding (requires @napi-rs/cli)
-cd bindings/node && npm install && npm run build && npm test
-```
-
-## Testing
-
-Every layer is covered; run the suites with the commands in
-[Building everything from source](#building-everything-from-source).
-
-- `wickra-core`: unit tests per indicator — textbook reference values
-  (Wilder RSI, Bollinger Bands, MACD, ATR, Stochastic), `batch == streaming`
-  equivalence, `reset` semantics, NaN/Inf handling, and property tests.
-- `wickra-data`: unit tests for CSV decoding, the tick aggregator, the
-  resampler, and the Binance payload parser.
-- `bindings/python`: pytest covering smoke checks, streaming/batch
-  equivalence, reference values, lifecycle, input validation, and
-  dict/tuple candle inputs.
-- `bindings/node`: `node --test` cases for batch, streaming, and reference
-  values across all indicators.
-- `bindings/wasm`: `wasm-bindgen-test` cases for constructors, equivalence,
-  and reference values.
-
-## Contributing
-
-Contributions are very welcome — issues, bug reports, ideas, and pull requests
-all land in the same place: <https://github.com/wickra-lib/wickra>.
-
-A short orientation for first-time contributors:
-
-- **Adding an indicator.** Implement the `Indicator` trait in
-  `crates/wickra-core/src/indicators/<name>.rs`, wire it into
-  `indicators/mod.rs` and the crate root, and add reference-value tests,
-  a `batch == streaming` equivalence test, and (where it makes sense) a
-  proptest. The four bindings inherit your indicator automatically once
-  you expose it in the language wrappers.
-- **Fixing a numeric bug.** Add a failing test that pins the textbook value
-  first, then fix the math. Property tests in `crates/wickra-core` catch
-  most regressions; please don't disable them.
-- **Improving a binding.** Each binding lives under `bindings/<lang>` with
-  its own tests; please keep the `batch == streaming` invariant.
-- **Style.** `cargo fmt --all` + `cargo clippy --workspace --all-targets -- -D warnings`
-  are CI gates; running them locally before pushing keeps reviews short.
-
-For larger architectural changes, open an issue first so we can sketch the
-shape together before you invest the time.
+Wickra is an indicator toolkit, not a trading system. The values it computes
+are deterministic transforms of the input data — they are not financial advice
+and do not predict the market. Any use in a live trading context is at your own
+risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. See [LICENSE](LICENSE).
-
-In plain English: use it, fork it, modify it, redistribute it, file issues, send
-pull requests — all welcome. Personal projects, research, education, non-profits,
-government, hobby trading bots: all fine. The one thing that's not allowed is
-commercial sale of the software or of services built around it. If you want to
-use Wickra commercially, get in touch about a license.
-
----
-
-<p align="center">
-  <a href="https://github.com/wickra-lib/wickra/stargazers">
-    <img alt="GitHub stars" src="https://img.shields.io/github/stars/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ffd866">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/network/members">
-    <img alt="GitHub forks" src="https://img.shields.io/github/forks/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=78dce8">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/issues">
-    <img alt="GitHub issues" src="https://img.shields.io/github/issues/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ff6188">
-  </a>
-</p>
-
-<p align="center">
-  If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
-</p>
+Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
+research, education, non-profits, and hobby trading bots are all fine; the one
+thing not allowed is commercial sale of the software or of services built
+around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).
diff --git a/bindings/python/README.md b/bindings/python/README.md
index 1450b719..fc19671d 100644
--- a/bindings/python/README.md
+++ b/bindings/python/README.md
@@ -1,314 +1,72 @@
-# Wickra
+# Wickra — Python
 
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
-[![crates.io](https://img.shields.io/crates/v/wickra.svg?logo=rust&color=orange)](https://crates.io/crates/wickra)
 [![PyPI](https://img.shields.io/pypi/v/wickra.svg?logo=pypi&color=blue)](https://pypi.org/project/wickra/)
-[![npm](https://img.shields.io/npm/v/wickra.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](LICENSE)
+[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
 
-**Streaming-first technical indicators. Install with `pip install wickra` — no system dependencies.**
+**Streaming-first technical indicators for Python. `pip install wickra` — no
+system dependencies, no C build tooling.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is a state
-machine that updates in O(1) per new data point, so live trading bots and
-historical backtests share the exact same implementation.
+bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1)
+streaming state machine, so live trading bots and historical backtests share
+the exact same implementation. This package is the Python binding (PyO3); it
+exposes 200+ streaming-first indicators across sixteen families.
+
+## Install
+
+```bash
+pip install wickra
+```
+
+Pre-built wheels ship for Linux, macOS, and Windows — there is nothing to
+compile and no C library to track down.
+
+## Quick start
 
 ```python
 import numpy as np
 import wickra as ta
 
-# Batch: classic TA-Lib-style usage
+# Batch: classic TA-Lib-style usage over a whole array.
 prices = np.linspace(100, 200, 1000)
 rsi = ta.RSI(14)
 values = rsi.batch(prices)              # numpy array, NaN during warmup
 
-# Streaming: same indicator, fed tick by tick
+# Streaming: the same indicator, fed tick by tick in O(1).
 rsi = ta.RSI(14)
 for price in live_feed:
-    value = rsi.update(price)           # O(1) — no recomputation over history
+    value = rsi.update(price)           # no recomputation over history
     if value is not None and value > 70:
         print("overbought")
 ```
 
-## Why Wickra exists
+`batch(prices)` and feeding the same prices through `update()` produce
+identical values — the equivalence is enforced by the test suite.
 
-The Python TA ecosystem has plenty of libraries — TA-Lib, pandas-ta, finta,
-talipp, tulipy — and every one of them shares the same blind spot:
+## Documentation
 
-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★&nbsp;Wickra**      | **clean**       | **yes**   | **Python + Node + WASM + Rust** | **yes** |
-| TA-Lib (Python)        | yes (C deps)    | no        | no             | barely |
-| pandas-ta              | clean           | no        | no             | slow   |
-| finta                  | clean           | no        | no             | stale  |
-| ta-lib-python          | yes (C deps)    | no        | no             | barely |
-| talipp                 | clean           | yes       | no             | yes    |
-| Tulip Indicators       | yes (C deps)    | no        | partial        | stale  |
-| ooples (C#)            | clean           | no        | C# only        | yes    |
+The full indicator catalogue, guides, quickstarts, and API reference live in
+the main repository and wiki:
 
-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Wiki** (quickstarts, cookbook, TA-Lib migration): <https://github.com/wickra-lib/wickra/wiki>
+- **Runnable examples:** [`examples/python/`](https://github.com/wickra-lib/wickra/tree/main/examples/python)
 
-## Benchmark: how much faster is "streaming-first"?
+Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
+expose the same indicators from the shared, `unsafe`-forbidden Rust core.
 
-The numbers below were measured on a single developer workstation and are not
-guaranteed to reproduce identically on different hardware — absolute µs values
-depend on CPU, memory clock and OS scheduler. Read them as **relative
-speedups** between libraries on identical input, not as a universal
-performance contract.
+## Disclaimer
 
-- **Reproduced on:** Windows 11 Pro 26200, AMD Ryzen 9 9950X, 64 GB DDR5,
-  Rust 1.92 (release profile, `lto = "fat"`, `codegen-units = 1`),
-  Python 3.12, Node 20.
-- **Reproduce yourself:** `pip install -e bindings/python[bench]` then
-  `python -m benchmarks.compare_libraries`. The script auto-detects every
-  installed peer library and runs them on the same generated inputs as
-  Wickra. The CI job `cross-library-bench` runs the same script on every
-  push and uploads the raw report as a build artefact.
-
-Lower µs/op = faster. Wickra wins every batch category outright, and the
-streaming gap widens linearly with how much history a batch-only library has
-to recompute on every tick.
-
-### Batch — single full pass over a 20 000-bar series
-
-Reading the table: each cell shows that library's runtime, plus how many times
-slower it is than Wickra in parentheses. **★** marks the winner per row.
-
-| Indicator           | **★&nbsp;Wickra**   | finta                       | talipp                        |
-|---------------------|---------------------|-----------------------------|-------------------------------|
-| SMA(20)             | **95.6 µs ★**       | 343.5 µs (3.6× slower)      | 7 640.6 µs (79.9× slower)     |
-| EMA(20)             | **64.6 µs ★**       | 223.1 µs (3.5× slower)      | 12 160.9 µs (188.2× slower)   |
-| RSI(14)             | **126.2 µs ★**      | 1 107.1 µs (8.8× slower)    | 15 792.2 µs (125.1× slower)   |
-| MACD(12, 26, 9)     | **119.0 µs ★**      | 531.8 µs (4.5× slower)      | 49 788.1 µs (418.2× slower)   |
-| Bollinger(20, 2.0)  | **105.3 µs ★**      | 812.0 µs (7.7× slower)      | 130 938.3 µs (1 243.7× slower)|
-| ATR(14)             | **123.5 µs ★**      | 5 144.8 µs (41.7× slower)   | 28 816.0 µs (233.4× slower)   |
-
-### Streaming — per-tick latency after seeding with 5 000 historical bars
-
-A batch-only library has to re-run its full indicator over the entire history on
-every new tick; Wickra updates state in O(1).
-
-| Indicator | **★&nbsp;Wickra (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
-
-> TA-Lib and pandas-ta are not included here because both fail to install
-> cleanly on Windows without C build tooling — which is precisely the install
-> pain Wickra was built to remove. The benchmark script auto-detects every
-> peer library it can find and runs them on the same inputs as Wickra; install
-> them in your environment to see those rows light up too.
-
-Run the suite yourself:
-
-```bash
-pip install -e bindings/python[bench]
-python -m benchmarks.compare_libraries
-```
-
-## Indicators
-
-214 streaming-first indicators across sixteen families. Every one passes the
-`batch == streaming` equivalence test, reference-value tests, and reset
-semantics tests.
-
-| Family | Indicators |
-|--------|-----------|
-| Moving Averages      | SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA, ALMA, McGinley Dynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA |
-| Momentum Oscillators | RSI (Wilder), Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator, RVI, PGO, KST, SMI, Laguerre RSI, Connors RSI, Inertia |
-| Trend & Directional  | MACD, ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter |
-| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC |
-| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility, Detrended StdDev |
-| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands |
-| Trailing Stops       | Parabolic SAR, SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop |
-| Volume               | OBV, VWAP (cumulative + rolling), ADL, Volume-Price Trend, Chaikin Money Flow, Chaikin Oscillator, Force Index, Ease of Movement, Klinger Volume Oscillator, Volume Oscillator, NVI, PVI, Williams A/D, Anchored VWAP, Demand Index, TSV, VZO, Market Facilitation Index |
-| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Spearman Correlation |
-| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline |
-| Pivots & S/R         | Classic Pivots, Fibonacci Pivots, Camarilla, Woodie Pivots, DeMark Pivots, Williams Fractals, ZigZag |
-| DeMark               | TD Setup, TD Sequential, TD DeMarker, TD REI, TD Pressure, TD Combo, TD Countdown, TD Lines, TD Range Projection, TD Differential, TD Open, TD Risk Level |
-| Ichimoku & Charts    | Ichimoku Kinko Hyo (Tenkan, Kijun, Senkou A/B, Chikou), Heikin-Ashi |
-| Candlestick Patterns | Doji, Hammer, Inverted Hammer, Hanging Man, Shooting Star, Engulfing, Harami, Morning/Evening Star, Three White Soldiers/Black Crows, Piercing Line/Dark Cloud Cover, Marubozu, Tweezer, Spinning Top, Three Inside Up/Down, Three Outside Up/Down |
-| Market Profile       | Value Area (POC / VAH / VAL), Initial Balance, Opening Range |
-| Risk / Performance   | Sharpe Ratio, Sortino Ratio, Calmar Ratio, Omega Ratio, Max Drawdown, Average Drawdown, Drawdown Duration, Pain Index, Value at Risk, Conditional Value at Risk (CVaR), Profit Factor, Gain/Loss Ratio, Recovery Factor, Kelly Criterion, Treynor Ratio, Information Ratio, Alpha (Jensen) |
-
-Adding a new indicator means implementing one trait in Rust; all four bindings
-inherit it automatically.
-
-## Languages
-
-| Binding           | Install                                       | Example |
-|-------------------|-----------------------------------------------|---------|
-| Python (PyO3)     | `pip install wickra`                          | `examples/python/backtest.py` |
-| Node.js (napi-rs) | `npm install wickra`                          | `examples/node/backtest.js` |
-| Browser / WASM    | `npm install wickra-wasm`                     | `examples/wasm/index.html` |
-| Rust              | `cargo add wickra`                            | `examples/rust/src/bin/backtest.rs` |
-
-Each binding ships several runnable examples (streaming, backtest, live feed);
-[`examples/README.md`](examples/README.md) is the full cross-language index.
-
-The wickra-core crate is `unsafe`-forbidden, so every binding inherits a
-memory-safe implementation.
-
-## Rust API
-
-```rust
-use wickra::{Indicator, BatchExt, Chain, Ema, Rsi, Sma};
-
-// Streaming or batch — same trait, same code.
-let mut sma = Sma::new(14)?;
-let out: Vec<Option<f64>> = sma.batch(&[1.0, 2.0, 3.0, 4.0, 5.0]);
-
-let mut rsi = Rsi::new(14)?;
-for price in live_feed {
-    if let Some(v) = rsi.update(price) {
-        println!("RSI = {v}");
-    }
-}
-
-// Compose indicators: RSI(7) on top of EMA(14).
-let mut chain = Chain::new(Ema::new(14)?, Rsi::new(7)?);
-chain.update(price);
-```
-
-## Live data sources
-
-`wickra-data` (separate crate, opt-in) ships:
-
-- A streaming OHLCV **CSV reader**.
-- A **tick-to-candle aggregator** with arbitrary timeframes.
-- A **candle resampler** for multi-timeframe analysis (1m → 5m → 1h on the fly).
-- A **Binance Spot WebSocket** kline adapter (feature `live-binance`).
-
-```rust
-use wickra::{Indicator, Rsi};
-use wickra_data::live::binance::{BinanceKlineStream, Interval};
-
-let mut stream = BinanceKlineStream::connect(&["BTCUSDT".into()], Interval::OneMinute).await?;
-let mut rsi = Rsi::new(14)?;
-while let Some(event) = stream.next_event().await? {
-    if event.is_closed {
-        if let Some(v) = rsi.update(event.candle.close) {
-            println!("RSI = {v:.2}");
-        }
-    }
-}
-```
-
-A Python live-trading example using the public `websockets` package lives at
-`examples/python/live_trading.py`.
-
-## Project layout
-
-```
-wickra/
-├── crates/
-│   ├── wickra-core/         core engine + all 71 indicators
-│   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
-├── bindings/
-│   ├── python/              PyO3 + maturin (publishes on PyPI)
-│   ├── node/                napi-rs (publishes on npm)
-│   └── wasm/                wasm-bindgen (browsers, bundlers, Node)
-├── examples/                examples/README.md indexes every language
-│   ├── data/                real BTCUSDT OHLCV datasets, one per timeframe
-│   ├── rust/                Rust workspace member (`wickra-examples`)
-│   ├── python/              backtest, live trading, parallel assets, multi-tf
-│   ├── node/                streaming, backtest, live trading (load `wickra`)
-│   └── wasm/                browser demo for `wickra-wasm`
-└── .github/workflows/       CI and release pipelines
-```
-
-Rust benchmarks live in `crates/wickra/benches/`; runnable Rust examples live
-in the workspace member crate at `examples/rust/`. There is no top-level
-`benches/` directory.
-
-## Building everything from source
-
-```bash
-# Rust core + tests
-cargo test --workspace
-cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
-
-# Python binding (requires Rust toolchain + maturin)
-cd bindings/python
-maturin develop --release
-pytest
-
-# WASM binding (requires wasm-pack + wasm32-unknown-unknown target)
-wasm-pack build bindings/wasm --target web --release --features panic-hook
-
-# Node binding (requires @napi-rs/cli)
-cd bindings/node && npm install && npm run build && npm test
-```
-
-## Testing
-
-Every layer is covered; run the suites with the commands in
-[Building everything from source](#building-everything-from-source).
-
-- `wickra-core`: unit tests per indicator — textbook reference values
-  (Wilder RSI, Bollinger Bands, MACD, ATR, Stochastic), `batch == streaming`
-  equivalence, `reset` semantics, NaN/Inf handling, and property tests.
-- `wickra-data`: unit tests for CSV decoding, the tick aggregator, the
-  resampler, and the Binance payload parser.
-- `bindings/python`: pytest covering smoke checks, streaming/batch
-  equivalence, reference values, lifecycle, input validation, and
-  dict/tuple candle inputs.
-- `bindings/node`: `node --test` cases for batch, streaming, and reference
-  values across all indicators.
-- `bindings/wasm`: `wasm-bindgen-test` cases for constructors, equivalence,
-  and reference values.
-
-## Contributing
-
-Contributions are very welcome — issues, bug reports, ideas, and pull requests
-all land in the same place: <https://github.com/wickra-lib/wickra>.
-
-A short orientation for first-time contributors:
-
-- **Adding an indicator.** Implement the `Indicator` trait in
-  `crates/wickra-core/src/indicators/<name>.rs`, wire it into
-  `indicators/mod.rs` and the crate root, and add reference-value tests,
-  a `batch == streaming` equivalence test, and (where it makes sense) a
-  proptest. The four bindings inherit your indicator automatically once
-  you expose it in the language wrappers.
-- **Fixing a numeric bug.** Add a failing test that pins the textbook value
-  first, then fix the math. Property tests in `crates/wickra-core` catch
-  most regressions; please don't disable them.
-- **Improving a binding.** Each binding lives under `bindings/<lang>` with
-  its own tests; please keep the `batch == streaming` invariant.
-- **Style.** `cargo fmt --all` + `cargo clippy --workspace --all-targets -- -D warnings`
-  are CI gates; running them locally before pushing keeps reviews short.
-
-For larger architectural changes, open an issue first so we can sketch the
-shape together before you invest the time.
+Wickra is an indicator toolkit, not a trading system. The values it computes
+are deterministic transforms of the input data — they are not financial advice
+and do not predict the market. Any use in a live trading context is at your own
+risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. See [LICENSE](LICENSE).
-
-In plain English: use it, fork it, modify it, redistribute it, file issues, send
-pull requests — all welcome. Personal projects, research, education, non-profits,
-government, hobby trading bots: all fine. The one thing that's not allowed is
-commercial sale of the software or of services built around it. If you want to
-use Wickra commercially, get in touch about a license.
-
----
-
-<p align="center">
-  <a href="https://github.com/wickra-lib/wickra/stargazers">
-    <img alt="GitHub stars" src="https://img.shields.io/github/stars/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ffd866">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/network/members">
-    <img alt="GitHub forks" src="https://img.shields.io/github/forks/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=78dce8">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/issues">
-    <img alt="GitHub issues" src="https://img.shields.io/github/issues/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ff6188">
-  </a>
-</p>
-
-<p align="center">
-  If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
-</p>
+Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
+research, education, non-profits, and hobby trading bots are all fine; the one
+thing not allowed is commercial sale of the software or of services built
+around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).
diff --git a/bindings/wasm/README.md b/bindings/wasm/README.md
index 1450b719..6fdc0dff 100644
--- a/bindings/wasm/README.md
+++ b/bindings/wasm/README.md
@@ -1,314 +1,72 @@
-# Wickra
+# Wickra — WebAssembly
 
 [![CI](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml/badge.svg)](https://github.com/wickra-lib/wickra/actions/workflows/ci.yml)
 [![codecov](https://codecov.io/gh/wickra-lib/wickra/branch/main/graph/badge.svg)](https://codecov.io/gh/wickra-lib/wickra)
-[![crates.io](https://img.shields.io/crates/v/wickra.svg?logo=rust&color=orange)](https://crates.io/crates/wickra)
-[![PyPI](https://img.shields.io/pypi/v/wickra.svg?logo=pypi&color=blue)](https://pypi.org/project/wickra/)
-[![npm](https://img.shields.io/npm/v/wickra.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra)
-[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](LICENSE)
+[![npm](https://img.shields.io/npm/v/wickra-wasm.svg?logo=npm&color=red)](https://www.npmjs.com/package/wickra-wasm)
+[![License: PolyForm-NC](https://img.shields.io/badge/license-PolyForm--NC--1.0.0-purple)](https://github.com/wickra-lib/wickra/blob/main/LICENSE)
 
-**Streaming-first technical indicators. Install with `pip install wickra` — no system dependencies.**
+**Streaming-first technical indicators in the browser. `npm install
+wickra-wasm` — pure WebAssembly, runs anywhere a modern JS engine does.**
 
 Wickra is a multi-language technical-analysis library with a Rust core and
-bindings for Python, Node.js, and WebAssembly. Every indicator is a state
-machine that updates in O(1) per new data point, so live trading bots and
-historical backtests share the exact same implementation.
+bindings for Python, Node.js, and WebAssembly. Every indicator is an O(1)
+streaming state machine, so live trading dashboards and historical backtests
+share the exact same implementation. This package is the WebAssembly binding
+(wasm-bindgen, built for the `web` target); it exposes 200+ streaming-first
+indicators across sixteen families.
 
-```python
-import numpy as np
-import wickra as ta
-
-# Batch: classic TA-Lib-style usage
-prices = np.linspace(100, 200, 1000)
-rsi = ta.RSI(14)
-values = rsi.batch(prices)              # numpy array, NaN during warmup
-
-# Streaming: same indicator, fed tick by tick
-rsi = ta.RSI(14)
-for price in live_feed:
-    value = rsi.update(price)           # O(1) — no recomputation over history
-    if value is not None and value > 70:
-        print("overbought")
-```
-
-## Why Wickra exists
-
-The Python TA ecosystem has plenty of libraries — TA-Lib, pandas-ta, finta,
-talipp, tulipy — and every one of them shares the same blind spot:
-
-| Library                | Install pain    | Streaming | Multi-language | Active |
-|------------------------|-----------------|-----------|----------------|--------|
-| **★&nbsp;Wickra**      | **clean**       | **yes**   | **Python + Node + WASM + Rust** | **yes** |
-| TA-Lib (Python)        | yes (C deps)    | no        | no             | barely |
-| pandas-ta              | clean           | no        | no             | slow   |
-| finta                  | clean           | no        | no             | stale  |
-| ta-lib-python          | yes (C deps)    | no        | no             | barely |
-| talipp                 | clean           | yes       | no             | yes    |
-| Tulip Indicators       | yes (C deps)    | no        | partial        | stale  |
-| ooples (C#)            | clean           | no        | C# only        | yes    |
-
-Wickra is the only library that combines all of: clean install, streaming,
-multi-language reach, and active maintenance.
-
-## Benchmark: how much faster is "streaming-first"?
-
-The numbers below were measured on a single developer workstation and are not
-guaranteed to reproduce identically on different hardware — absolute µs values
-depend on CPU, memory clock and OS scheduler. Read them as **relative
-speedups** between libraries on identical input, not as a universal
-performance contract.
-
-- **Reproduced on:** Windows 11 Pro 26200, AMD Ryzen 9 9950X, 64 GB DDR5,
-  Rust 1.92 (release profile, `lto = "fat"`, `codegen-units = 1`),
-  Python 3.12, Node 20.
-- **Reproduce yourself:** `pip install -e bindings/python[bench]` then
-  `python -m benchmarks.compare_libraries`. The script auto-detects every
-  installed peer library and runs them on the same generated inputs as
-  Wickra. The CI job `cross-library-bench` runs the same script on every
-  push and uploads the raw report as a build artefact.
-
-Lower µs/op = faster. Wickra wins every batch category outright, and the
-streaming gap widens linearly with how much history a batch-only library has
-to recompute on every tick.
-
-### Batch — single full pass over a 20 000-bar series
-
-Reading the table: each cell shows that library's runtime, plus how many times
-slower it is than Wickra in parentheses. **★** marks the winner per row.
-
-| Indicator           | **★&nbsp;Wickra**   | finta                       | talipp                        |
-|---------------------|---------------------|-----------------------------|-------------------------------|
-| SMA(20)             | **95.6 µs ★**       | 343.5 µs (3.6× slower)      | 7 640.6 µs (79.9× slower)     |
-| EMA(20)             | **64.6 µs ★**       | 223.1 µs (3.5× slower)      | 12 160.9 µs (188.2× slower)   |
-| RSI(14)             | **126.2 µs ★**      | 1 107.1 µs (8.8× slower)    | 15 792.2 µs (125.1× slower)   |
-| MACD(12, 26, 9)     | **119.0 µs ★**      | 531.8 µs (4.5× slower)      | 49 788.1 µs (418.2× slower)   |
-| Bollinger(20, 2.0)  | **105.3 µs ★**      | 812.0 µs (7.7× slower)      | 130 938.3 µs (1 243.7× slower)|
-| ATR(14)             | **123.5 µs ★**      | 5 144.8 µs (41.7× slower)   | 28 816.0 µs (233.4× slower)   |
-
-### Streaming — per-tick latency after seeding with 5 000 historical bars
-
-A batch-only library has to re-run its full indicator over the entire history on
-every new tick; Wickra updates state in O(1).
-
-| Indicator | **★&nbsp;Wickra (per tick)** | talipp (per tick)         |
-|-----------|---------------------|---------------------------|
-| RSI(14)   | **0.119 µs ★**      | 1.644 µs (13.8× slower)   |
-
-> TA-Lib and pandas-ta are not included here because both fail to install
-> cleanly on Windows without C build tooling — which is precisely the install
-> pain Wickra was built to remove. The benchmark script auto-detects every
-> peer library it can find and runs them on the same inputs as Wickra; install
-> them in your environment to see those rows light up too.
-
-Run the suite yourself:
+## Install
 
 ```bash
-pip install -e bindings/python[bench]
-python -m benchmarks.compare_libraries
+npm install wickra-wasm
 ```
 
-## Indicators
+## Quick start
 
-214 streaming-first indicators across sixteen families. Every one passes the
-`batch == streaming` equivalence test, reference-value tests, and reset
-semantics tests.
+The module ships a default `init` export that loads the `.wasm` payload; await
+it once before constructing indicators.
 
-| Family | Indicators |
-|--------|-----------|
-| Moving Averages      | SMA, EMA, WMA, DEMA, TEMA, HMA, KAMA, SMMA, TRIMA, ZLEMA, T3, VWMA, ALMA, McGinley Dynamic, FRAMA, VIDYA, JMA, Alligator, EVWMA |
-| Momentum Oscillators | RSI (Wilder), Stochastic, CCI, ROC, Williams %R, MFI, Awesome Oscillator, MOM, CMO, TSI, PMO, StochRSI, Ultimate Oscillator, RVI, PGO, KST, SMI, Laguerre RSI, Connors RSI, Inertia |
-| Trend & Directional  | MACD, ADX (+DI/-DI), ADXR, Aroon, TRIX, Aroon Oscillator, Vortex, Random Walk Index, Trend Intensity Index, Wave Trend Oscillator, Mass Index, Choppiness Index, Vertical Horizontal Filter |
-| Price Oscillators    | PPO, DPO, Coppock, Accelerator Oscillator, Balance of Power, APO, AO Histogram, CFO, Zero-Lag MACD, Elder Impulse, STC |
-| Volatility & Bands   | ATR, Bollinger Bands, Keltner Channels, Donchian Channels, NATR, StdDev, Ulcer Index, Historical Volatility, Bollinger Bandwidth, %B, True Range, Chaikin Volatility, RVI (Relative Volatility Index), Parkinson Volatility, Garman-Klass Volatility, Rogers-Satchell Volatility, Yang-Zhang Volatility, Detrended StdDev |
-| Bands & Channels     | MA Envelope, Acceleration Bands, STARC Bands, ATR Bands, Hurst Channel, LinReg Channel, Standard Error Bands, Double Bollinger Bands, TTM Squeeze, Fractal Chaos Bands, VWAP StdDev Bands |
-| Trailing Stops       | Parabolic SAR, SuperTrend, Chandelier Exit, Chande Kroll Stop, ATR Trailing Stop, HiLo Activator, Volty Stop, Yo-Yo Exit, Donchian Channel Stop, Percentage Trailing Stop, Step Trailing Stop, Renko Trailing Stop |
-| Volume               | OBV, VWAP (cumulative + rolling), ADL, Volume-Price Trend, Chaikin Money Flow, Chaikin Oscillator, Force Index, Ease of Movement, Klinger Volume Oscillator, Volume Oscillator, NVI, PVI, Williams A/D, Anchored VWAP, Demand Index, TSV, VZO, Market Facilitation Index |
-| Price Statistics     | Typical Price, Median Price, Weighted Close, Linear Regression, Linear Regression Slope, Z-Score, Linear Regression Angle, Variance, Coefficient of Variation, Skewness, Kurtosis, Standard Error, R², Median Absolute Deviation, Autocorrelation, Hurst Exponent, Pearson Correlation, Beta, Spearman Correlation |
-| Ehlers / Cycle (DSP) | MAMA, FAMA, Fisher Transform, Inverse Fisher Transform, SuperSmoother, Hilbert Dominant Cycle, Sine Wave, Decycler, Decycler Oscillator, Roofing Filter, Center of Gravity, Cybernetic Cycle, Adaptive Cycle, Empirical Mode Decomposition, Ehlers Stochastic, Instantaneous Trendline |
-| Pivots & S/R         | Classic Pivots, Fibonacci Pivots, Camarilla, Woodie Pivots, DeMark Pivots, Williams Fractals, ZigZag |
-| DeMark               | TD Setup, TD Sequential, TD DeMarker, TD REI, TD Pressure, TD Combo, TD Countdown, TD Lines, TD Range Projection, TD Differential, TD Open, TD Risk Level |
-| Ichimoku & Charts    | Ichimoku Kinko Hyo (Tenkan, Kijun, Senkou A/B, Chikou), Heikin-Ashi |
-| Candlestick Patterns | Doji, Hammer, Inverted Hammer, Hanging Man, Shooting Star, Engulfing, Harami, Morning/Evening Star, Three White Soldiers/Black Crows, Piercing Line/Dark Cloud Cover, Marubozu, Tweezer, Spinning Top, Three Inside Up/Down, Three Outside Up/Down |
-| Market Profile       | Value Area (POC / VAH / VAL), Initial Balance, Opening Range |
-| Risk / Performance   | Sharpe Ratio, Sortino Ratio, Calmar Ratio, Omega Ratio, Max Drawdown, Average Drawdown, Drawdown Duration, Pain Index, Value at Risk, Conditional Value at Risk (CVaR), Profit Factor, Gain/Loss Ratio, Recovery Factor, Kelly Criterion, Treynor Ratio, Information Ratio, Alpha (Jensen) |
+```js
+import init, { RSI } from 'wickra-wasm';
 
-Adding a new indicator means implementing one trait in Rust; all four bindings
-inherit it automatically.
+await init(); // load the WebAssembly module once
 
-## Languages
-
-| Binding           | Install                                       | Example |
-|-------------------|-----------------------------------------------|---------|
-| Python (PyO3)     | `pip install wickra`                          | `examples/python/backtest.py` |
-| Node.js (napi-rs) | `npm install wickra`                          | `examples/node/backtest.js` |
-| Browser / WASM    | `npm install wickra-wasm`                     | `examples/wasm/index.html` |
-| Rust              | `cargo add wickra`                            | `examples/rust/src/bin/backtest.rs` |
-
-Each binding ships several runnable examples (streaming, backtest, live feed);
-[`examples/README.md`](examples/README.md) is the full cross-language index.
-
-The wickra-core crate is `unsafe`-forbidden, so every binding inherits a
-memory-safe implementation.
-
-## Rust API
-
-```rust
-use wickra::{Indicator, BatchExt, Chain, Ema, Rsi, Sma};
-
-// Streaming or batch — same trait, same code.
-let mut sma = Sma::new(14)?;
-let out: Vec<Option<f64>> = sma.batch(&[1.0, 2.0, 3.0, 4.0, 5.0]);
-
-let mut rsi = Rsi::new(14)?;
-for price in live_feed {
-    if let Some(v) = rsi.update(price) {
-        println!("RSI = {v}");
-    }
-}
-
-// Compose indicators: RSI(7) on top of EMA(14).
-let mut chain = Chain::new(Ema::new(14)?, Rsi::new(7)?);
-chain.update(price);
-```
-
-## Live data sources
-
-`wickra-data` (separate crate, opt-in) ships:
-
-- A streaming OHLCV **CSV reader**.
-- A **tick-to-candle aggregator** with arbitrary timeframes.
-- A **candle resampler** for multi-timeframe analysis (1m → 5m → 1h on the fly).
-- A **Binance Spot WebSocket** kline adapter (feature `live-binance`).
-
-```rust
-use wickra::{Indicator, Rsi};
-use wickra_data::live::binance::{BinanceKlineStream, Interval};
-
-let mut stream = BinanceKlineStream::connect(&["BTCUSDT".into()], Interval::OneMinute).await?;
-let mut rsi = Rsi::new(14)?;
-while let Some(event) = stream.next_event().await? {
-    if event.is_closed {
-        if let Some(v) = rsi.update(event.candle.close) {
-            println!("RSI = {v:.2}");
-        }
-    }
+// Streaming: feed prices tick by tick in O(1).
+const rsi = new RSI(14);
+for (const price of liveFeed) {
+  const value = rsi.update(price); // null during warmup
+  if (value !== null && value > 70) {
+    console.log('overbought');
+  }
 }
 ```
 
-A Python live-trading example using the public `websockets` package lives at
-`examples/python/live_trading.py`.
+Constructors mirror the other bindings (`new SMA(20)`, `new MACD(12, 26, 9)`,
+`new BollingerBands(20, 2.0)`, …); `update()` returns the latest value or
+`null` while the indicator is still warming up.
 
-## Project layout
+## Documentation
 
-```
-wickra/
-├── crates/
-│   ├── wickra-core/         core engine + all 71 indicators
-│   ├── wickra/              top-level facade crate (publishes on crates.io) + benches/
-│   └── wickra-data/         CSV reader, tick aggregator, live exchange feeds
-├── bindings/
-│   ├── python/              PyO3 + maturin (publishes on PyPI)
-│   ├── node/                napi-rs (publishes on npm)
-│   └── wasm/                wasm-bindgen (browsers, bundlers, Node)
-├── examples/                examples/README.md indexes every language
-│   ├── data/                real BTCUSDT OHLCV datasets, one per timeframe
-│   ├── rust/                Rust workspace member (`wickra-examples`)
-│   ├── python/              backtest, live trading, parallel assets, multi-tf
-│   ├── node/                streaming, backtest, live trading (load `wickra`)
-│   └── wasm/                browser demo for `wickra-wasm`
-└── .github/workflows/       CI and release pipelines
-```
+The full indicator catalogue, guides, quickstarts, and API reference live in
+the main repository and wiki:
 
-Rust benchmarks live in `crates/wickra/benches/`; runnable Rust examples live
-in the workspace member crate at `examples/rust/`. There is no top-level
-`benches/` directory.
+- **Repository & full indicator list:** <https://github.com/wickra-lib/wickra>
+- **Wiki** (quickstarts, cookbook, TA-Lib migration): <https://github.com/wickra-lib/wickra/wiki>
+- **Runnable browser examples:** [`examples/wasm/`](https://github.com/wickra-lib/wickra/tree/main/examples/wasm)
 
-## Building everything from source
+Wickra ships four bindings — Python, Node.js, WebAssembly, and Rust — that all
+expose the same indicators from the shared, `unsafe`-forbidden Rust core.
 
-```bash
-# Rust core + tests
-cargo test --workspace
-cargo clippy --workspace --all-targets -- -D warnings
-cargo bench -p wickra
+## Disclaimer
 
-# Python binding (requires Rust toolchain + maturin)
-cd bindings/python
-maturin develop --release
-pytest
-
-# WASM binding (requires wasm-pack + wasm32-unknown-unknown target)
-wasm-pack build bindings/wasm --target web --release --features panic-hook
-
-# Node binding (requires @napi-rs/cli)
-cd bindings/node && npm install && npm run build && npm test
-```
-
-## Testing
-
-Every layer is covered; run the suites with the commands in
-[Building everything from source](#building-everything-from-source).
-
-- `wickra-core`: unit tests per indicator — textbook reference values
-  (Wilder RSI, Bollinger Bands, MACD, ATR, Stochastic), `batch == streaming`
-  equivalence, `reset` semantics, NaN/Inf handling, and property tests.
-- `wickra-data`: unit tests for CSV decoding, the tick aggregator, the
-  resampler, and the Binance payload parser.
-- `bindings/python`: pytest covering smoke checks, streaming/batch
-  equivalence, reference values, lifecycle, input validation, and
-  dict/tuple candle inputs.
-- `bindings/node`: `node --test` cases for batch, streaming, and reference
-  values across all indicators.
-- `bindings/wasm`: `wasm-bindgen-test` cases for constructors, equivalence,
-  and reference values.
-
-## Contributing
-
-Contributions are very welcome — issues, bug reports, ideas, and pull requests
-all land in the same place: <https://github.com/wickra-lib/wickra>.
-
-A short orientation for first-time contributors:
-
-- **Adding an indicator.** Implement the `Indicator` trait in
-  `crates/wickra-core/src/indicators/<name>.rs`, wire it into
-  `indicators/mod.rs` and the crate root, and add reference-value tests,
-  a `batch == streaming` equivalence test, and (where it makes sense) a
-  proptest. The four bindings inherit your indicator automatically once
-  you expose it in the language wrappers.
-- **Fixing a numeric bug.** Add a failing test that pins the textbook value
-  first, then fix the math. Property tests in `crates/wickra-core` catch
-  most regressions; please don't disable them.
-- **Improving a binding.** Each binding lives under `bindings/<lang>` with
-  its own tests; please keep the `batch == streaming` invariant.
-- **Style.** `cargo fmt --all` + `cargo clippy --workspace --all-targets -- -D warnings`
-  are CI gates; running them locally before pushing keeps reviews short.
-
-For larger architectural changes, open an issue first so we can sketch the
-shape together before you invest the time.
+Wickra is an indicator toolkit, not a trading system. The values it computes
+are deterministic transforms of the input data — they are not financial advice
+and do not predict the market. Any use in a live trading context is at your own
+risk. The library is provided **as is**, without warranty of any kind.
 
 ## License
 
-Licensed under the **PolyForm Noncommercial License 1.0.0**. See [LICENSE](LICENSE).
-
-In plain English: use it, fork it, modify it, redistribute it, file issues, send
-pull requests — all welcome. Personal projects, research, education, non-profits,
-government, hobby trading bots: all fine. The one thing that's not allowed is
-commercial sale of the software or of services built around it. If you want to
-use Wickra commercially, get in touch about a license.
-
----
-
-<p align="center">
-  <a href="https://github.com/wickra-lib/wickra/stargazers">
-    <img alt="GitHub stars" src="https://img.shields.io/github/stars/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ffd866">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/network/members">
-    <img alt="GitHub forks" src="https://img.shields.io/github/forks/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=78dce8">
-  </a>
-  <a href="https://github.com/wickra-lib/wickra/issues">
-    <img alt="GitHub issues" src="https://img.shields.io/github/issues/wickra-lib/wickra?style=for-the-badge&logo=github&logoColor=white&color=ff6188">
-  </a>
-</p>
-
-<p align="center">
-  If Wickra saved you time, the cheapest way to say thanks is to ⭐ the repo.
-</p>
+Licensed under the **PolyForm Noncommercial License 1.0.0**. Personal projects,
+research, education, non-profits, and hobby trading bots are all fine; the one
+thing not allowed is commercial sale of the software or of services built
+around it. See [LICENSE](https://github.com/wickra-lib/wickra/blob/main/LICENSE).