Main Agent Supervisor
/install main-agent-supervisor
Main Agent Supervisor
This skill is for a supervisor layer over a main agent, not a generic task tracker.
Goal
Prevent the main agent from getting stuck on obvious decisions while still preserving real human control for risky or ambiguous actions.
Core design
Use a four-part model:
-
Classifier
- Decide whether a pending ask/action is:
AUTOCONFIRMESCALATE
- Decide whether a pending ask/action is:
-
Pre-send gate
- Before the main agent sends a user-visible reply, ask:
- Is this asking for an obvious decision?
- Is there a safe default?
- Is the agent permission-looping?
- If yes, suppress the question and continue execution.
- Before the main agent sends a user-visible reply, ask:
-
Triage / watchdog
- Borrowing from
claude-code-supervisor, classify agent state into:FINENEEDS_NUDGESTUCKDONEESCALATE
- Use a lightweight pre-filter for obvious cases before invoking heavier review.
- Borrowing from
-
Task-state tracking for large tasks
- Borrowing from
task-supervisor, keep simple checkpoint files for long tasks. - Track:
- started time
- status
- completed steps
- last updated
- current blocker / next step
- Borrowing from
Use this policy
AUTO
Proceed without bothering the user when all are true:
- internal / local action
- reversible or low-risk
- no external send/publish
- no payment / secret / production change
- user intent is already clear
- there is one reasonable default
CONFIRM
Ask the user when any are true:
- external send/publish
- destructive / irreversible action
- money / orders / account changes
- production/live-system changes
- privacy / compliance / legal sensitivity
ESCALATE
Ask only when blocked after reasonable retries or when multiple materially different paths exist.
Reply-shaping rules
When the main agent drafts a question, rewrite it if:
- it is merely asking permission for an AUTO action
- it asks for a trivial preference that has a safe default
- it proposes extra scope that is obviously worth trying and reversible
Preferred rewrite:
- state the chosen default
- continue execution
- mention assumptions briefly if needed
For larger tasks, pair this with a task-state file instead of ad-hoc check-in messages. That preserves progress visibility without interrupting the user for obvious decisions.
Best current pattern
For this workspace, the best practical setup is:
- escalation classifier as the core policy
- pre-send gate as enforcement
- triage/watchdog for stuck detection
- task-state files for large tasks
- passive reviewer/audit log for tuning
References
Read these when needed:
references/design.md— recommended architecture and message flowreferences/comparison.md— what existing public skills cover vs what they missreferences/implementation.md— workspace-specific OpenClaw implementation plan
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install main-agent-supervisor - After installation, invoke the skill by name or use
/main-agent-supervisor - Provide required inputs per the skill's parameter spec and get structured output
What is Main Agent Supervisor?
Supervise a main agent so it defaults to execution, suppresses obvious permission loops, and escalates to the user only for true approvals or critical ambigu... It is an AI Agent Skill for Claude Code / OpenClaw, with 309 downloads so far.
How do I install Main Agent Supervisor?
Run "/install main-agent-supervisor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Main Agent Supervisor free?
Yes, Main Agent Supervisor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Main Agent Supervisor support?
Main Agent Supervisor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Main Agent Supervisor?
It is built and maintained by sjinopenclaw (@sjingh); the current version is v0.1.0.