docs(docs): add YouTube video and detailed monotonic stack explanation with Python example

apps/docs/content/(01-linear-structures)/monotonic-stack/index.mdx

@@ -3,3 +3,34 @@ title: Monotonic Stack
 description: 'A stack keeps its items in sorted order, which finds the next larger or smaller item in one pass.'
 hidden: true
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+
+
+<YouTube id="Dq_ObZwTY_Q" title="Monotonic Stack" />
+
+A monotonic stack keeps its values in sorted order as you push elements. The order can be increasing or decreasing, depending on the problem.
+
+A decreasing monotonic stack is the most common version. Before pushing a new value `x`, we pop from the top while the top is smaller than or equal to `x`. After those pops, pushing `x` keeps the stack decreasing from bottom to top.
+
+This push rule is the whole idea. A monotonic deque uses the same rule, but a deque also lets you remove old elements from the front, which is useful for sliding window problems.
+
+## Example Implementation
+
+This implementation maintains a decreasing monotonic stack.
+
+```python
+def mono_stack(insert_entries):
+    stack = []
+    for entry in insert_entries:
+        # Pop smaller (or equal) values so stack stays decreasing.
+        while stack and stack[-1] <= entry:
+            stack.pop()
+            # Do something with the popped item here
+        stack.append(entry)
+```
+
+:::tip
+In interview problems, the stack usually stores indices instead of values. You can read the value from the original array when needed, and the index gives you distance information such as **"how many steps away is the next greater element."**
+:::
+
+For an array `nums`, if index `j` pops when you process index `i`, then `i` is the first index to the right that satisfies the stack condition for `j`. In a next-greater-element problem, that means `nums[i]` is the next greater value for `nums[j]`.
+