fix: correct grammar in guardrail, task output, and prompt templates

lib/crewai/src/crewai/task.py

@@ -162,7 +162,7 @@ class Task(BaseModel):
         default=True,
     )
     output: TaskOutput | None = Field(
-        description="Task output, it's final result after being executed", default=None
+        description="Task output, its final result after being executed", default=None
     )
     tools: list[BaseTool] | None = Field(
         default_factory=list,

lib/crewai/src/crewai/tasks/llm_guardrail.py

@@ -41,7 +41,7 @@ class LLMGuardrailResult(BaseModel):
         description="Whether the task output complies with the guardrail"
     )
     feedback: str | None = Field(
-        description="A feedback about the task output if it is not valid",
+        description="Feedback about the task output if it is not valid",
         default=None,
     )
 
@@ -50,11 +50,11 @@ class LLMGuardrail:
     """It validates the output of another task using an LLM.
 
     This class is used to validate the output from a Task based on specified criteria.
-    It uses an LLM to validate the output and provides a feedback if the output is not valid.
+    It uses an LLM to validate the output and provides feedback if the output is not valid.
 
     Args:
         description (str): The description of the validation criteria.
-        llm (LLM, optional): The language model to use for code generation.
+        llm (LLM, optional): The language model to use for validation.
     """
 
     def __init__(
@@ -70,7 +70,7 @@ def _validate_output(self, task_output: TaskOutput) -> LiteAgentOutput:
         agent = Agent(
             role="Guardrail Agent",
             goal="Validate the output of the task",
-            backstory="You are a expert at validating the output of a task. By providing effective feedback if the output is not valid.",
+            backstory="You are an expert at validating the output of a task by providing effective feedback if the output is not valid.",
             llm=self.llm,
         )
 
@@ -87,7 +87,7 @@ def _validate_output(self, task_output: TaskOutput) -> LiteAgentOutput:
         - Confirm if the Task result complies with the guardrail.
         - If not, provide clear feedback explaining what is wrong (e.g., by how much it violates the rule, or what specific part fails).
         - Focus only on identifying issues — do not propose corrections.
-        - If the Task result complies with the guardrail, saying that is valid
+        - If the Task result complies with the guardrail, say that it is valid
         """
 
         kickoff_result = agent.kickoff(query, response_format=LLMGuardrailResult)

lib/crewai/src/crewai/translations/en.json

@@ -17,7 +17,7 @@
     "post_tool_reasoning": "Analyze the tool result. If requirements are met, provide the Final Answer. Otherwise, call the next tool. Deliver only the answer without meta-commentary.",
     "format": "Decide if you need a tool or can provide the final answer. Use one at a time.\nTo use a tool, use:\nThought: [reasoning]\nAction: [name from {tool_names}]\nAction Input: [JSON object]\n\nTo provide the final answer, use:\nThought: [reasoning]\nFinal Answer: [complete response]",
     "final_answer_format": "If you don't need to use any more tools, you must give your best complete final answer, make sure it satisfies the expected criteria, use the EXACT format below:\n\n```\nThought: I now can give a great answer\nFinal Answer: my best complete final answer to the task.\n\n```",
-    "format_without_tools": "\nSorry, I didn't use the right format. I MUST either use a tool (among the available ones), OR give my best final answer.\nHere is the expected format I must follow:\n\n```\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to take, should be one of [{tool_names}]\nAction Input: the input to the action\nObservation: the result of the action\n```\n This Thought/Action/Action Input/Result process can repeat N times. Once I know the final answer, I must return the following format:\n\n```\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described\n\n```",
+    "format_without_tools": "\nSorry, I didn't use the right format. I MUST either use a tool (among the available ones), OR give my best final answer.\nHere is the expected format I must follow:\n\n```\nQuestion: the input question you must answer\nThought: you should always think about what to do\nAction: the action to take, should be one of [{tool_names}]\nAction Input: the input to the action\nObservation: the result of the action\n```\n This Thought/Action/Action Input/Result process can repeat N times. Once I know the final answer, I must return the following format:\n\n```\nThought: I now can give a great answer\nFinal Answer: Your final answer must be as great and complete as possible, it must be the outcome described\n\n```",
     "task_with_context": "{task}\n\nThis is the context you're working with:\n{context}",
     "expected_output": "\nThis is the expected criteria for your final answer: {expected_output}\nyou MUST return the actual complete content as the final answer, not a summary.",
     "human_feedback": "You got human feedback on your work, re-evaluate it and give a new Final Answer when ready.\n {human_feedback}",
@@ -30,7 +30,7 @@
     "conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals.",
     "feedback_instructions": "User feedback: {feedback}\nInstructions: Use this feedback to enhance the next output iteration.\nNote: Do not respond or add commentary.",
     "lite_agent_system_prompt_with_tools": "You are {role}. {backstory}\nYour personal goal is: {goal}\n\nYou ONLY have access to the following tools, and should NEVER make up tools that are not listed here:\n\n{tools}\n\nIMPORTANT: Use the following format in your response:\n\n```\nThought: you should always think about what to do\nAction: the action to take, only one name of [{tool_names}], just the name, exactly as it's written.\nAction Input: the input to the action, just a simple JSON object, enclosed in curly braces, using \" to wrap keys and values.\nObservation: the result of the action\n```\n\nOnce all necessary information is gathered, return the following format:\n\n```\nThought: I now know the final answer\nFinal Answer: the final answer to the original input question\n```",
-    "lite_agent_system_prompt_without_tools": "You are {role}. {backstory}\nYour personal goal is: {goal}\n\nTo give my best complete final answer to the task respond using the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be the great and the most complete as possible, it must be outcome described.\n\nI MUST use these formats, my job depends on it!",
+    "lite_agent_system_prompt_without_tools": "You are {role}. {backstory}\nYour personal goal is: {goal}\n\nTo give my best complete final answer to the task respond using the exact following format:\n\nThought: I now can give a great answer\nFinal Answer: Your final answer must be as great and complete as possible, it must be the outcome described.\n\nI MUST use these formats, my job depends on it!",
     "lite_agent_response_format": "Format your final answer according to the following OpenAPI schema: {response_format}\n\nIMPORTANT: Preserve the original content exactly as-is. Do NOT rewrite, paraphrase, or modify the meaning of the content. Only structure it to match the schema format.\n\nDo not include the OpenAPI schema in the final output. Ensure the final output does not include any code block markers like ```json or ```python.",
     "knowledge_search_query": "The original query is: {task_prompt}.",
     "knowledge_search_query_system_prompt": "Your goal is to rewrite the user query so that it is optimized for retrieval from a vector database. Consider how the query will be used to find relevant documents, and aim to make it more specific and context-aware. \n\n Do not include any other text than the rewritten query, especially any preamble or postamble and only add expected output format if its relevant to the rewritten query. \n\n Focus on the key words of the intended task and to retrieve the most relevant information. \n\n There will be some extra context provided that might need to be removed such as expected_output formats structured_outputs and other instructions.",