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Main Agent Supervisor

作者 sjinopenclaw · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install main-agent-supervisor
功能描述
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...
使用说明 (SKILL.md)

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:

  • 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 flow
  • references/comparison.md — what existing public skills cover vs what they miss
  • references/implementation.md — workspace-specific OpenClaw implementation plan
安全使用建议
This skill is internally coherent and doesn't request secrets, but review and accept its policy implications before use: (1) confirm you are comfortable with the supervisor auto-executing low-risk 'AUTO' actions without prompting; (2) expect it to create workspace files under .tasks/ and artifacts/supervisor/ (backup or audit those if needed); (3) do not enable Phase 2 (cron jobs or a hook pack that intercepts outgoing replies) until you have inspected the hook implementation and explicitly opt in; and (4) consider logging/audit retention so you can review decisions the supervisor made.
功能分析
Type: OpenClaw Skill Name: main-agent-supervisor Version: 0.1.0 The main-agent-supervisor skill is a workflow optimization tool designed to manage agent autonomy by classifying actions into AUTO, CONFIRM, or ESCALATE categories. Its primary goal is to prevent 'permission loops' by allowing the agent to proceed with low-risk, reversible, and internal tasks without redundant user prompts. The implementation plan (implementation.md) and design (design.md) utilize standard OpenClaw features such as cron jobs for task monitoring and local file storage for state tracking (.tasks/ and artifacts/ folders), with no evidence of data exfiltration, malicious execution, or unauthorized persistence.
能力评估
Purpose & Capability
The name/description match the instructions: this is a policy/supervisor layer that classifies replies (AUTO/CONFIRM/ESCALATE), keeps lightweight task files, and suggests a phased implementation. It does not request unrelated credentials, binaries, or external services.
Instruction Scope
SKILL.md instructs the agent to create workspace files (.tasks/* and artifacts/supervisor/*), run periodic checks (cron), and potentially rewrite/suppress user-visible questions for AUTO-classified actions. It does not instruct reading secret env vars or contacting external endpoints, but it does explicitly permit proceeding without user confirmation for low-risk AUTO actions — a policy decision with safety implications the user should review.
Install Mechanism
Instruction-only skill with no install spec, no downloads, and no code files. Nothing is written to disk by an installer; file writes mentioned are part of runtime behavior and are limited to workspace paths.
Credentials
Requires no environment variables, keys, or external credentials. The only state it proposes to persist is workspace task/checkpoint files and audit artifacts; these are proportionate to the stated purpose.
Persistence & Privilege
always:false and normal autonomous invocation. However Phase 2 recommends adding cron-based watchdogs and an optional hook pack that would intercept outgoing replies — those steps increase system presence and should be enabled only with explicit review and understanding of the hook implementation.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install main-agent-supervisor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /main-agent-supervisor 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
Initial release: policy brain, task-state workflow, watchdog plan, and Phase 2 outbound audit hook guidance.
元数据
Slug main-agent-supervisor
版本 0.1.0
许可证 MIT-0
累计安装 2
当前安装数 2
历史版本数 1
常见问题

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。

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