Restore helpful comments in documentation code examples

Co-authored-by: Samuel <samuel@knutsen.co>

Author: cursoragent

AGENTS_DOC.md

@@ -158,35 +158,49 @@ from tensorbored.plugins.core import profile_writer, color_sampler
 
 p = profile_writer.create_profile(
     'Training Monitor',
+
+    # Pin your most important metrics at the top
     pinned_cards=[
         profile_writer.pin_scalar('train/loss'),
         profile_writer.pin_scalar('eval/loss'),
         profile_writer.pin_scalar('train/accuracy'),
         profile_writer.pin_scalar('eval/accuracy'),
         profile_writer.pin_scalar('learning_rate'),
     ],
+
+    # Create comparison charts
     superimposed_cards=[
         profile_writer.create_superimposed_card(
             title='Train vs Eval Loss',
             tags=['train/loss', 'eval/loss'],
         ),
     ],
+
+    # Assign colors to runs
     run_colors={
         'baseline': '#9E9E9E',
         'experiment_v1': '#2196F3',
         'experiment_v2': '#4CAF50',
     },
+
+    # Add metric descriptions (shown as hover tooltips)
     metric_descriptions={
         'train/loss': 'Cross-entropy loss on the training set.',
         'eval/loss': 'Cross-entropy loss on the held-out validation set.',
         'learning_rate': 'Effective learning rate after warmup and cosine decay.',
     },
+
+    # Default filter and smoothing
     tag_filter='loss|accuracy|learning_rate',
     smoothing=0.8,
+
+    # Group runs by regex pattern
     group_by={
         'key': 'regex',
         'regexString': r'(baseline|experiment)',
     },
+
+    # Control which sections are expanded on load
     expanded_tag_groups={
         'train': True,
         'eval': True,

README.md

@@ -98,6 +98,7 @@ Set up default dashboard configurations from your training code using the
 ```python
 from tensorbored.plugins.core import profile_writer
 
+# Create a profile for your experiment
 p = profile_writer.create_profile(
     'Training Monitor',
     pinned_cards=[
@@ -117,6 +118,8 @@ p = profile_writer.create_profile(
         'eval/accuracy': 'Top-1 accuracy on the validation set.',
     },
 )
+
+# Writes to <logdir>/.tensorboard/default_profile.json
 p.write('/path/to/logs')
 ```