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crewai - 💡(How to fix) Fix [FEATURE] Add pre-execution validation for agent-to-agent actions

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Feature Area

Other (please specify in additional context)

Is your feature request related to a an existing bug? Please link it here.

no

Describe the solution you'd like

CrewAI enables multi-agent workflows where agents collaborate and trigger actions across tasks and tools.

In these systems, actions can propagate between agents before ultimately resulting in execution (tool calls, API requests, etc).

It would be valuable to have a deterministic validation step at the moment of execution to ensure consistency and correctness of actions across agent interactions.

In multi-agent workflows:

  • actions generated by one agent are passed to another
  • parameters may evolve across interactions
  • execution depends on the final payload produced at runtime

Adding validation at the execution boundary would help ensure that the final action being executed is complete, expected, and consistent with system constraints.

Suggested approach

Introduce a validation step before execution that verifies:

  • originating agent and receiving agent
  • action being performed
  • parameters (schema + expected values)
  • destination or external system
  • timestamp / validity window
  • optional nonce or replay protection

If validation fails → execution does not occur.

This could be implemented as a wrapper around execution functions or as a system-level layer to ensure consistent behavior across agent interactions.

Describe alternatives you've considered

Validation can be implemented within individual tasks or agents, but this makes enforcement optional and inconsistent across workflows.

A system-level validation layer would ensure consistent behavior regardless of how individual agents or tasks are configured.

Additional context

As multi-agent workflows become more complex, actions can pass through multiple layers before execution.

Having a consistent validation step at the execution boundary would help ensure predictable and reliable behavior across all agent interactions.

Willingness to Contribute

Yes, I'd be happy to submit a pull request

extent analysis

TL;DR

Introduce a validation step before execution to verify the consistency and correctness of actions across agent interactions in multi-agent workflows.

Guidance

  • Identify the key parameters to be validated, such as originating agent, receiving agent, action, parameters, destination, and timestamp.
  • Design a validation function or layer that can be applied consistently across all agent interactions, potentially as a wrapper around execution functions.
  • Consider implementing a system-level validation layer to ensure consistent behavior regardless of individual agent or task configurations.
  • Evaluate the trade-offs between validation complexity and performance impact on the workflow execution.

Example

def validate_action(action):
    # Example validation function
    required_fields = ['originating_agent', 'receiving_agent', 'action', 'parameters']
    if not all(field in action for field in required_fields):
        return False
    # Additional validation logic can be added here
    return True

Notes

The proposed solution requires careful consideration of the validation logic and its potential impact on workflow performance. The example provided is a simplified illustration and may need to be adapted to the specific requirements of the multi-agent workflow system.

Recommendation

Apply a workaround by introducing a validation step before execution, as this will provide a more consistent and reliable behavior across all agent interactions, even if it may require additional development and testing efforts.

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