diff --git a/langchain/chains/llm_for_loop.py b/langchain/chains/llm_for_loop.py
index 7c2b63d060a..e47813bc78b 100644
--- a/langchain/chains/llm_for_loop.py
+++ b/langchain/chains/llm_for_loop.py
@@ -1,10 +1,11 @@
+"""Chain that first uses an LLM to generate multiple items then loops over them."""
+from typing import Any, Dict, List
 
-from typing import Dict, List, Any
-
-from pydantic import BaseModel, Extra
+from pydantic import BaseModel, Extra, root_validator
 
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
+from langchain.prompts.base import ListOutputParser
 
 
 class LLMForLoopChain(Chain, BaseModel):
@@ -38,6 +39,17 @@ class LLMForLoopChain(Chain, BaseModel):
         """
         return [self.output_key]
 
+    @root_validator()
+    def validate_output_parser(cls, values: Dict) -> Dict:
+        """Validate that the correct inputs exist for all chains."""
+        chain = values["llm_chain"]
+        if not isinstance(chain.prompt.output_parser, ListOutputParser):
+            raise ValueError(
+                f"The OutputParser on the base prompt should be of type "
+                f"ListOutputParser, got {type(chain.prompt.output_parser)}"
+            )
+        return values
+
     def run_list(self, **kwargs: Any) -> List[str]:
         """Get list from LLM chain and then run chain on each item."""
         output_items = self.llm_chain.predict_and_parse(**kwargs)
diff --git a/langchain/prompts/base.py b/langchain/prompts/base.py
index 849ea926e62..22a385ec1fa 100644
--- a/langchain/prompts/base.py
+++ b/langchain/prompts/base.py
@@ -1,8 +1,8 @@
 """BasePrompt schema definition."""
 from abc import ABC, abstractmethod
-from typing import Any, Dict, List, Union, Optional
+from typing import Any, Dict, List, Optional, Union
 
-from pydantic import BaseModel, Field, root_validator, Extra
+from pydantic import BaseModel, Extra, root_validator
 
 from langchain.formatting import formatter
 
@@ -37,6 +37,13 @@ class BaseOutputParser(ABC):
         """Parse the output of an LLM call."""
 
 
+class ListOutputParser(ABC):
+    """Class to parse the output of an LLM call to a list."""
+
+    @abstractmethod
+    def parse(self, text: str) -> List[str]:
+        """Parse the output of an LLM call."""
+
 
 class BasePromptTemplate(BaseModel, ABC):
     """Base prompt should expose the format method, returning a prompt."""