-Performance is one of the main target of these worker pool implementations, we want to have a strong focus on this.
-We already have a bench folder where you can find some comparisons.
-To choose your pool consider that with a FixedThreadPool/FixedClusterPool or a DynamicThreadPool/DynamicClusterPool (in this case is important the min parameter passed to the constructor) your application memory footprint will increase.
-Increasing the memory footprint, your application will be ready to accept more CPU bound tasks, but during idle time your application will consume more memory.
-One good choose from my point of view is to profile your application using Fixed/Dynamic worker pool, and to see your application metrics when you increase/decrease the num of workers.
-For example you could keep the memory footprint low choosing a DynamicThreadPool/DynamicClusterPool with 5 workers, and allow to create new workers until 50/100 when needed, this is the advantage to use the DynamicThreadPool/DynamicClusterPool.
-But in general, **always profile your application**
+#### `YourWorker.addTaskFunction(name, fn)`
+
+`name` (mandatory) The task function name
+`fn` (mandatory) The task function
+
+This method is available on both worker implementations and returns a boolean.
+
+#### `YourWorker.removeTaskFunction(name)`
+
+`name` (mandatory) The task function name
+
+This method is available on both worker implementations and returns a boolean.
+
+#### `YourWorker.listTaskFunctions()`
+
+This method is available on both worker implementations and returns an array of the task function names.
+
+#### `YourWorker.setDefaultTaskFunction(name)`
+
+`name` (mandatory) The task function name
+
+This method is available on both worker implementations and returns a boolean.
+
+## General guidance
+
+Performance is one of the main target of these worker pool implementations, poolifier team wants to have a strong focus on this.
+Poolifier already has a [benchmarks](./benchmarks/) folder where you can find some comparisons.
+
+### Internal Node.js thread pool
+
+Before to jump into each poolifier pool type, let highlight that **Node.js comes with a thread pool already**, the libuv thread pool where some particular tasks already run by default.
+Please take a look at [which tasks run on the libuv thread pool](https://nodejs.org/en/docs/guides/dont-block-the-event-loop/#what-code-runs-on-the-worker-pool).
+
+**If your task runs on libuv thread pool**, you can try to:
+
+- Tune the libuv thread pool size setting the [UV_THREADPOOL_SIZE](https://nodejs.org/api/cli.html#cli_uv_threadpool_size_size).
+
+and/or
+
+- Use poolifier cluster pools that are spawning child processes, they will also increase the number of libuv threads since that any new child process comes with a separated libuv thread pool. **More threads does not mean more fast, so please tune your application**.
+
+### Cluster vs Threads worker pools
+
+**If your task does not run into libuv thread pool** and is CPU intensive then poolifier **thread pools** (_FixedThreadPool_ and _DynamicThreadPool_) are suggested to run CPU intensive tasks, you can still run I/O intensive tasks into thread pools, but performance enhancement is expected to be minimal.
+Thread pools are built on top of Node.js [worker_threads](https://nodejs.org/api/worker_threads.html) module.
+
+**If your task does not run into libuv thread pool** and is I/O intensive then poolifier **cluster pools** (_FixedClusterPool_ and _DynamicClusterPool_) are suggested to run I/O intensive tasks, again you can still run CPU intensive tasks into cluster pools, but performance enhancement is expected to be minimal.
+Consider that by default Node.js already has great performance for I/O tasks (asynchronous I/O).
+Cluster pools are built on top of Node.js [cluster](https://nodejs.org/api/cluster.html) module.
+
+If your task contains code that runs on libuv plus code that is CPU intensive or I/O intensive you either split it either combine more strategies (i.e. tune the number of libuv threads and use cluster/thread pools).
+But in general, **always profile your application**.
+
+### Fixed vs Dynamic pools
+
+To choose your pool consider first that with a _FixedThreadPool_/_FixedClusterPool_ or a _DynamicThreadPool_/_DynamicClusterPool_ your application memory footprint will increase.
+By doing so, your application will be ready to execute in parallel more tasks, but during idle time your application will consume more memory.
+One good choice from poolifier team point of view is to profile your application using a static or dynamic worker pool, and analyze your application metrics when you increase/decrease the number of workers.
+For example you could keep the memory footprint low by choosing a _DynamicThreadPool_/_DynamicClusterPool_ with a minimum of 5 workers, and allowing it to create new workers until a maximum of 50 workers if needed. This is the advantage of using a _DynamicThreadPool_/_DynamicClusterPool_.
+But in general, **always profile your application**.