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
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install main-agent-supervisor - 安装完成后,直接呼叫该 Skill 的名称或使用
/main-agent-supervisor触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Main Agent Supervisor 是什么?
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... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 309 次。
如何安装 Main Agent Supervisor?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install main-agent-supervisor」即可一键安装,无需额外配置。
Main Agent Supervisor 是免费的吗?
是的,Main Agent Supervisor 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
Main Agent Supervisor 支持哪些平台?
Main Agent Supervisor 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Main Agent Supervisor?
由 sjinopenclaw(@sjingh)开发并维护,当前版本 v0.1.0。