diff --git a/examples/simple_event_writer.json b/examples/simple_event_writer.json
new file mode 100644
index 00000000000..3dd4d7f7334
--- /dev/null
+++ b/examples/simple_event_writer.json
@@ -0,0 +1,9 @@
+{
+  "Analysis": {
+    "allowed_tels": [1, 2, 3, 4]
+  },
+  "Preselect": {
+    "image_amplitude": {"min": 50},
+    "n_pixel": {"min": 3}
+  }
+}
\ No newline at end of file
diff --git a/examples/simple_event_writer.py b/examples/simple_event_writer.py
new file mode 100755
index 00000000000..51975d3ac22
--- /dev/null
+++ b/examples/simple_event_writer.py
@@ -0,0 +1,115 @@
+#!/usr/bin/env python3
+"""
+This example uses a configuration file in JSON format to
+process the events and apply pre-selection cuts to the images
+(charge and number of pixels).
+An HDF5 file is written with image MC and moment parameters
+(e.g. length, width, image amplitude, etc.).
+"""
+
+import numpy as np
+from tqdm import tqdm
+
+from ctapipe.core import Tool
+from ctapipe.core.traits import Unicode, List, Dict, Bool
+from ctapipe.io import EventSourceFactory, HDF5TableWriter
+from ctapipe.calib import CameraCalibrator
+from ctapipe.utils.CutFlow import CutFlow
+from ctapipe.image import hillas_parameters, tailcuts_clean
+
+
+class SimpleEventWriter(Tool):
+    name = 'ctapipe-simple-event-writer'
+    description = Unicode(__doc__)
+
+    infile = Unicode(help='input file to read', default='').tag(config=True)
+    outfile = Unicode(help='output file name', default_value='output.h5').tag(config=True)
+    progress = Bool(help='display progress bar', default_value=True).tag(config=True)
+
+    aliases = Dict({
+        'infile': 'EventSourceFactory.input_url',
+        'outfile': 'SimpleEventWriter.outfile',
+        'max-events': 'EventSourceFactory.max_events',
+        'progress': 'SimpleEventWriter.progress'
+    })
+    classes = List([EventSourceFactory, CameraCalibrator, CutFlow])
+
+    def setup(self):
+        self.log.info('Configure EventSourceFactory...')
+
+        self.event_source = EventSourceFactory.produce(
+            config=self.config, tool=self, product='HESSIOEventSource'
+        )
+        self.event_source.allowed_tels = self.config['Analysis']['allowed_tels']
+
+        self.calibrator = CameraCalibrator(
+            config=self.config, tool=self, eventsource=self.event_source
+        )
+
+        self.writer = HDF5TableWriter(
+            filename=self.outfile, group_name='image_infos', overwrite=True
+        )
+
+        # Define Pre-selection for images
+        preselcuts = self.config['Preselect']
+        self.image_cutflow = CutFlow('Image preselection')
+        self.image_cutflow.set_cuts(dict(
+            no_sel=None,
+            n_pixel=lambda s: np.count_nonzero(s) < preselcuts['n_pixel']['min'],
+            image_amplitude=lambda q: q < preselcuts['image_amplitude']['min']
+        ))
+
+        # Define Pre-selection for events
+        self.event_cutflow = CutFlow('Event preselection')
+        self.event_cutflow.set_cuts(dict(
+            no_sel=None
+        ))
+
+    def start(self):
+        self.log.info('Loop on events...')
+
+        for event in tqdm(
+                self.event_source,
+                desc='EventWriter',
+                total=self.event_source.max_events,
+                disable=~self.progress):
+
+            self.event_cutflow.count('no_sel')
+            self.calibrator.calibrate(event)
+
+            for tel_id in event.dl0.tels_with_data:
+                self.image_cutflow.count('no_sel')
+
+                camera = event.inst.subarray.tel[tel_id].camera
+                dl1_tel = event.dl1.tel[tel_id]
+
+                # Image cleaning
+                image = dl1_tel.image[0]  # Waiting for automatic gain selection
+                mask = tailcuts_clean(camera, image, picture_thresh=10, boundary_thresh=5)
+                cleaned = image.copy()
+                cleaned[~mask] = 0
+
+                # Preselection cuts
+                if self.image_cutflow.cut('n_pixel', cleaned):
+                    continue
+                if self.image_cutflow.cut('image_amplitude', np.sum(cleaned)):
+                    continue
+
+                # Image parametrisation
+                params = hillas_parameters(camera, cleaned, container=True)
+
+                # Save Ids, MC infos and Hillas informations
+                self.writer.write(camera.cam_id, [event.r0, event.mc, params])
+
+    def finish(self):
+        self.log.info('End of job.')
+
+        self.image_cutflow()
+        self.event_cutflow()
+        self.writer.close()
+
+
+if __name__ == '__main__':
+    tool = SimpleEventWriter()
+    tool.run()
+