crewAIInc / crewAIInc/crewAI

[FEATURE] Runtime release-control mediation layer before agent/tool execution

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feature-request
Dominant language
Python
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Description

Feature Area

Core functionality

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

N/A

Describe the solution you'd like

I’ve been experimenting with a lightweight runtime mediation layer for agent execution systems.

Core idea:
generation != release authority

Instead of treating every generated tool/action call as implicitly authorized, introduce a bounded runtime release-control layer between:

candidate generation
→ execution authorization

The mediation layer exposes tri-state runtime decisions:

  • PROCEED
  • NEEDS_REVIEW
  • SILENCE

The goal is not to block autonomous workflows entirely.

The goal is introducing a lightweight execution review boundary before unstable, unsafe, or high-risk execution paths.

This becomes especially relevant for:

  • external tool execution
  • browser actions
  • shell/code execution
  • long-running autonomous crews
  • recursive task delegation
  • multi-agent execution chains

Potential integration points could include:

  • tool-call authorization hooks
  • runtime middleware
  • task execution mediation
  • execution policy evaluators
  • bounded human-review escalation

I recently built a small live runtime demo around this direction:
https://silence-as-control.vibenest.net/

Curious whether CrewAI contributors are exploring similar runtime governance / execution mediation patterns for production-grade agent systems.

Describe alternatives you've considered

Most current systems appear to rely on:

  • prompt-level alignment
  • post-execution validation
  • static permission systems
  • sandbox isolation

The issue is that generation itself often becomes implicit execution authority.

I’m exploring whether a separate runtime release layer can reduce unsafe-path execution without fully removing agent autonomy.

Additional context

This is not intended as:

  • AGI framing
  • full autonomy suppression
  • centralized policy enforcement

More as:
runtime execution mediation
+
bounded release governance
for agent/tool execution systems.

Willingness to Contribute

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

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

No file, test, or concrete entry point is named. Start by locating the tool-call authorization hooks, runtime middleware, task execution mediation, and policy evaluators mentioned in the issue. Define the PROCEED, NEEDS_REVIEW, and SILENCE behavior and tests before implementation; done requires an agreed integration boundary.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai, security
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Active
Clarity
Needs clarification
Newbie friendliness
25/100

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