Main Agent Supervisor
by @sjingh
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...
clawhub install main-agent-supervisorπ About This Skill
name: main-agent-supervisor description: Supervise a main agent so it defaults to execution, suppresses obvious permission loops, and escalates to the user only for true approvals or critical ambiguity. Use when designing, running, or auditing a reviewer/gatekeeper/coaching layer for agent replies, approval policy, escalation logic, anti-stuck behavior, or supervisor-style chat/output filtering.
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:
1. Classifier
- Decide whether a pending ask/action is:
- AUTO
- CONFIRM
- ESCALATE
2. 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.
3. Triage / watchdog
- Borrowing from claude-code-supervisor, classify agent state into:
- FINE
- NEEDS_NUDGE
- STUCK
- DONE
- ESCALATE
- Use a lightweight pre-filter for obvious cases before invoking heavier review.
4. 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
Use this policy
AUTO
Proceed without bothering the user when all are true:CONFIRM
Ask the user when any are true: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:
Preferred rewrite:
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:
References
Read these when needed:
references/design.md β recommended architecture and message flowreferences/comparison.md β what existing public skills cover vs what they missreferences/implementation.md β workspace-specific OpenClaw implementation plan