openclaw - ✅(Solved) Fix Feature: managed agents layer for long-lived delegated work [1 pull requests, 1 comments, 1 participants]

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openclaw/openclaw#63310Fetched 2026-04-09 07:55:25
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Root Cause

This would make OpenClaw feel much more like an actual multi-agent operating system instead of a toolkit where the human has to keep recreating the manager layer manually.

Fix Action

Fixed

PR fix notes

PR #2620: docs: add Clauditor security watchdog documentation

Description (problem / solution / changelog)

Summary

Adds documentation for Clauditor, a tamper-resistant audit watchdog for Clawdbot VPS deployments.

Changes

  • New doc: docs/security/clauditor.md — Full documentation for Clauditor (installation, usage, security model)
  • Updated: docs/vps.md — Added "Hardening your VPS" section referencing SSH hardening, fail2ban, and Clauditor

Why

When running Clawdbot on a production VPS with access to sensitive data, users should have visibility into agent activity. Clauditor provides:

  • HMAC hash-chained tamper-evident logs
  • Exec monitoring and exfiltration detection
  • Independent audit trail that survives agent compromise

This is especially relevant for users giving agents elevated permissions or access to credentials.

Links

Changed files

  • docs/security/clauditor.md (added, +105/-0)
  • docs/vps.md (modified, +12/-0)
RAW_BUFFERClick to expand / collapse

Pattern to steal

Inspired by the idea behind "Claude Managed Agents" style delegated agent workflows.

Problem

OpenClaw can already spawn subagents, ACP sessions, cron jobs, and durable task flows, but the user still has to think in low-level session mechanics more than they should.

There is a missing product layer for managed agents that feel like durable named workers with clear ownership, lifecycle, memory boundaries, and follow-up semantics.

Proposed feature

Add a managed-agents layer that supports:

  • durable named agents / roles
  • long-lived delegated work with explicit ownership
  • clean task inbox / outbox semantics
  • clear memory/context boundaries per managed agent
  • visibility into status, blockers, last activity, and outputs
  • easy escalation / handoff back to the user or another lane

Why this matters

This would make OpenClaw feel much more like an actual multi-agent operating system instead of a toolkit where the human has to keep recreating the manager layer manually.

Relationship to existing issues

  • likely belongs under #2620 (orchestration and multi-agent operator UX)
  • overlaps with chief-of-staff / orchestration UX, but is specifically about durable agent identities and lifecycle management

Acceptance ideas

  • define the minimum managed-agent object model
  • define how task assignment, lifecycle, and memory boundaries work
  • define how managed agents differ from raw sessions/subagents
  • produce a first implementation slice that is useful without requiring a giant new framework

extent analysis

TL;DR

Implement a managed-agents layer with durable named workers and clear ownership to simplify user interaction with OpenClaw.

Guidance

  • Define the minimum managed-agent object model to establish a foundation for the new layer.
  • Determine how task assignment, lifecycle, and memory boundaries will work for managed agents to ensure clear semantics.
  • Develop a first implementation slice that provides a useful subset of managed agent functionality without requiring a large new framework.
  • Consider how managed agents will differ from raw sessions/subagents to avoid redundancy and ensure a clear value proposition.
  • Explore how the managed-agents layer will integrate with existing features, such as cron jobs and durable task flows.

Example

No specific code example is provided, as the issue focuses on high-level design and requirements.

Notes

The implementation of the managed-agents layer will require careful consideration of the trade-offs between simplicity, flexibility, and performance. It may be helpful to create a prototype or proof-of-concept to validate the design before investing in a full implementation.

Recommendation

Apply a workaround by defining a minimal managed-agent object model and implementing a basic version of the managed-agents layer, focusing on the most critical features and use cases. This will allow for testing and refinement of the concept before investing in a full implementation.

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