BANANA REPUBLIC SKIRT WOMENS 0 GRAY A LINE STRETCH WOOL BLEND PLEATED SIDE ZIP. Some minor discoloration. Please see all photos.

Pattern: Solid
Closure: Zip
Occasion: Business, Casual, Workwear
Garment Care: Dry Clean Only
Size: 0
Color: Gray
Material: Wool
Accents: Pleated, Zipper
Brand: Banana Republic
Size Type: Regular
Department: Women
Type: Skirt
Skirt Length: Short
Theme: City, Preppy
Style: A-Line
Features: Lined, Stretch
Season: Fall, Winter
Country of Origin: Thailand

#travel

Output:
#women #solid #zip #business #wool #pleated #skirt #short #city #a-line #lined #fall #casual #workwear #zipper

---

Input:
#men #leather #belt #dress casual workwear sport #jacket #shirt #pants #sandals #shoes #black #dark #grey #blue #red #green #worn #stylish #comfortable #leather

Output:
#men #leather #belt #dress #workwear #jacket #shirt #pants #shoes #black #dark #grey #blue #red #green #worn #stylish #comfortable

Comment:
Did not fit: #sandals #sport #red #green #worn
---

Input:
#women #floral #dress #party #summer #beach #floral #pink #shorts #sunglasses #bohemian #casual #summer #sandal #floral #shorts #summer #beach #floral #

Output:
#women #floral #dress #summer #beach #floral #pink #shorts #sunglasses #bohemian #casual #summer #sandal #floral #shorts
```

```python
def get_tags_from_input(input_strings):
"""
Processes a list of strings containing mechanical tags and returns a list
of refined tags.

Args:
input_strings: A list of strings where each string represents a tag.

Returns:
A string containing comma-separated tags.
"""
refined_tags = []
for string in input_strings:
# Check for brand size and color
if "brand" in string:
refined_tags.append("#brand")
if "size" in string:
refined_tags.append("#size")
if "color" in string:
refined_tags.append("#color")

# Ignore aspects related to the item's brand
if "brand" not in string and "brand type" not in string:
refined_tags.append("#brand")

# Remove trailing whitespace and convert to lowercase
refined_tags.append("#" + "".join(s.strip().lower() for s in string).replace(" " ""))

# Remove tags with values of "n/a" "none" "undefined" etc.
refined_tags = [tag for tag in refined_tags if tag not in ("n/a" "none" "undefined")]

# Remove any tag that is a compound tag
refined_tags = [tag for tag in refined_tags if not (tag.startswith("#") and tag.endswith("#"))]

# Order by frequency and prioritize
refined_tags = sorted(refined_tags key=lambda tag: (tag.count("#") tag) reverse=True)

return " ".join(refined_tags)
```