diff --git a/athena/utils/llm_util.py b/athena/utils/llm_util.py
index f7c40f5..db02477 100644
--- a/athena/utils/llm_util.py
+++ b/athena/utils/llm_util.py
@@ -6,14 +6,39 @@
 
 
 def str_token_counter(text: str) -> int:
+    """Counts the number of tokens in a string using tiktoken's o200k_base encoding.
+
+    Args:
+        text: The input string to count tokens for.
+
+    Returns:
+        The number of tokens in the input string.
+    """
     enc = tiktoken.get_encoding("o200k_base")
     return len(enc.encode(text))
 
 
 def tiktoken_counter(messages: Sequence[BaseMessage]) -> int:
-    """Approximately reproduce https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
+    """Counts tokens across multiple message types using tiktoken tokenization.
+
+    Approximately reproduces the token counting methodology from OpenAI's cookbook:
+    https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb
+
+    Args:
+        messages: A sequence of BaseMessage objects (HumanMessage, AIMessage,
+                 ToolMessage, or SystemMessage) to count tokens for.
+
+    Returns:
+        The total number of tokens across all messages, including overhead tokens.
+
+    Raises:
+        ValueError: If an unsupported message type is encountered.
 
-    For simplicity only supports str Message.contents.
+    Notes:
+        - Uses a fixed overhead of 3 tokens for reply priming
+        - Adds 3 tokens per message for message formatting
+        - Adds 1 token per message name if present
+        - For simplicity, only supports string message contents
     """
     output_parser = StrOutputParser()
     num_tokens = 3  # every reply is primed with <|start|>assistant<|message|>