feat: add DBOS skills for TypeScript, Python, and Go (#94)

Add three DBOS SDK skills with reference documentation for building
reliable, fault-tolerant applications with durable workflows.

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

skills/dbos-python/references/queue-concurrency.md

@@ -0,0 +1,57 @@
+---
+title: Control Queue Concurrency
+impact: HIGH
+impactDescription: Prevents resource exhaustion with concurrent limits
+tags: queue, concurrency, worker_concurrency, limits
+---
+
+## Control Queue Concurrency
+
+Queues support worker-level and global concurrency limits to prevent resource exhaustion.
+
+**Incorrect (no concurrency control):**
+
+```python
+queue = Queue("heavy_tasks")  # No limits - could exhaust memory
+
+@DBOS.workflow()
+def memory_intensive_task(data):
+    # Uses lots of memory
+    pass
+```
+
+**Correct (worker concurrency):**
+
+```python
+# Each process runs at most 5 tasks from this queue
+queue = Queue("heavy_tasks", worker_concurrency=5)
+
+@DBOS.workflow()
+def memory_intensive_task(data):
+    pass
+```
+
+**Correct (global concurrency):**
+
+```python
+# At most 10 tasks run across ALL processes
+queue = Queue("limited_tasks", concurrency=10)
+```
+
+**In-order processing (sequential):**
+
+```python
+# Only one task at a time - guarantees order
+queue = Queue("sequential_queue", concurrency=1)
+
+@DBOS.step()
+def process_event(event):
+    pass
+
+def handle_event(event):
+    queue.enqueue(process_event, event)
+```
+
+Worker concurrency is recommended for most use cases. Global concurrency should be used carefully as pending workflows count toward the limit.
+
+Reference: [Managing Concurrency](https://docs.dbos.dev/python/tutorials/queue-tutorial#managing-concurrency)