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crewai - 💡(How to fix) Fix [Feature] Trust-verified task delegation with Agent Governance Toolkit

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Proposing a governance callback/middleware for CrewAI that enforces policy before agent task delegation, powered by the Agent Governance Toolkit (AGT) — v3.2.0 Public Preview, 9,500+ tests, 5 SDK languages.

Root Cause

Proposing a governance callback/middleware for CrewAI that enforces policy before agent task delegation, powered by the Agent Governance Toolkit (AGT) — v3.2.0 Public Preview, 9,500+ tests, 5 SDK languages.

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Summary

Proposing a governance callback/middleware for CrewAI that enforces policy before agent task delegation, powered by the Agent Governance Toolkit (AGT) — v3.2.0 Public Preview, 9,500+ tests, 5 SDK languages.

Problem

When CrewAI agents delegate tasks to other agents or invoke tools, there's no built-in mechanism to enforce organizational policies — e.g., which agents can delegate to whom, what data can flow between tasks, or whether human approval is required for sensitive operations.

Proposed Solution

AGT already ships an agentmesh-integrations package with CrewAI support. The integration provides:

  • Pre-delegation policy checks — Evaluate YAML/OPA policies before any task handoff
  • Agent identity verification — Verify trust scores between delegating and receiving agents
  • Audit trail — Automatic logging of all delegation decisions with policy evaluation results
  • Human-in-the-loop gates — Configurable approval workflows for high-risk delegations

Example Usage

`python from crewai import Crew from agt.integrations.crewai import GovernanceCallback

crew = Crew( agents=[...], tasks=[...], callbacks=[GovernanceCallback(policy="delegation-policy.yaml")] ) `

References

Would love feedback on the best hook points in CrewAI's delegation flow.

extent analysis

TL;DR

Integrate the Agent Governance Toolkit (AGT) middleware into CrewAI to enforce organizational policies before agent task delegation.

Guidance

  • Review the agentmesh-integrations package and its CrewAI support to understand the available policy checks and integrations.
  • Evaluate the GovernanceCallback class and its usage in the example code to determine the best way to implement policy checks in your specific use case.
  • Consider the types of policies that need to be enforced, such as agent delegation permissions, data flow restrictions, and human approval requirements.
  • Investigate the delegation-policy.yaml file and its structure to understand how to define and configure policies for the GovernanceCallback.

Example

from crewai import Crew
from agt.integrations.crewai import GovernanceCallback

# Define a sample policy file (delegation-policy.yaml)
# ...
crew = Crew(
    agents=[...],
    tasks=[...],
    callbacks=[GovernanceCallback(policy="delegation-policy.yaml")]
)

Notes

The proposed solution relies on the AGT middleware and its integration with CrewAI. The effectiveness of the solution depends on the quality and coverage of the policies defined in the delegation-policy.yaml file.

Recommendation

Apply the proposed workaround by integrating the AGT middleware into CrewAI, as it provides a flexible and configurable way to enforce organizational policies before agent task delegation.

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