Shadow Agent

SKILL运维和基础设施
运维和基础设施 未标注权限 许可证不明确

Use this skill when you need a background monitoring agent that watches the fleet, detects anomalies, and can intervene on command. Triggers: user says "shadow", "monitoring agent", "fleet watcher", "hoop command", "spike detection".

一句话选型结论

按资料字段整理

Shadow Agent是运维和基础设施类的 Agent Skill,安装方式:GitHub 仓库,权限级别未标注,许可证不明确,没有现成安装命令,需按说明手动放置 SKILL.md。技能本质是给模型读的说明书,效果取决于模型与客户端;装完先用一个小任务验证,再放进正式流程。

分类运维和基础设施 安装方式GitHub 仓库 权限级别未标注权限 许可证许可证不明确
累计安装 未标注 本周 未标注
GitHub 星标 未标注 仓库 wrongstack
下载量 未标注 技能市场下载数
权限级别 未标注权限 安装前请确认风险范围
许可证 许可证不明确 未说明

安装

GitHub 仓库
在支持 Skills 的客户端里执行,装完问一句「你有哪些技能」验证
  1. 1
    确认客户端支持

    确认你的客户端支持 Skills(Claude、Codex、Cursor 等),并升级到较新的版本。

  2. 2
    拿到技能文件

    按安装说明或仓库 README,把 SKILL.md 放到客户端的 skills 目录(一般一个技能一个文件夹)。

  3. 3
    刷新技能列表

    重新打开客户端,或刷新技能列表,让新放进来的技能被加载。

  4. 4
    验证是否生效

    问一句「你有哪些技能」,确认列表里出现它,再拿一个小任务试跑。

技能档案

运维和基础设施
字段来自技能仓库与公开索引,中文说明由本站标注
作者 / 维护方wrongstack仓库 wrongstack · 版本 未标注
宿主客户端未标注技能可被这些客户端加载
安装方式GitHub 仓库安装包 wrongstack/wrongstack
权限级别未标注权限安装前请确认风险范围
许可证未说明许可证不明确,商用前请自行确认条款
仓库可用性available技能仓库当前是否可访问
最近核验未标注上游最后核验时间 · 数据更新 2026-08-07
正文体量10.0 KBSKILL.md 原文大小,越大说明说明书写得越细

典型使用场景

3 类
按分类整理的常见用法,具体以 SKILL.md 为准
查服务与日志

按现象定位服务状态与日志线索。

写部署与巡检脚本

把重复的部署、巡检写成脚本。

故障排查

按步骤排查网络、依赖与配置。

选择建议

装之前先看这几条
按条目字段给出的判断,不替你决定用不用

值得选的地方

  • 基础信息齐全,可以先按说明装一个试试。

先想清楚的地方

  • 没有标注权限级别,实际能做什么要装好后确认。
  • 许可证不明确,商用或二次分发前先到仓库确认条款。
  • 没有现成安装命令,要按安装说明或仓库 README 手动放置。
  • 没有做站内核验,内容以作者仓库为准。
  • 技能只是说明书,实际效果取决于模型与客户端,装完先用小任务试一遍。

更适合

  • 需要在运维和基础设施场景里给模型补一套做法的人。
  • 愿意先读一遍 SKILL.md、确认它会让模型做什么的人。

不太适合

  • 对许可证要求很严、必须明确可商用的人。
  • 只想装完就自动变强、不打算看说明书的人。

同类对比

6 个同类
同分类里挑最接近的几条,字段以各自详情页为准
技能权限级别安装方式累计安装宿主客户端安装命令
Shadow Agent当前 未标注权限 GitHub 仓库 未标注 未标注 无
Azure 部署 调用外部服务 GitHub 仓库 664.2 万 Codex、Claude、Cursor 有
Azure diagnostics 问题管理 调用外部服务 GitHub 仓库 657.6 万 Codex、Claude、Cursor 有
Azure aigateway 部署 调用外部服务 GitHub 仓库 655.3 万 Codex、Claude、Cursor 有
Azure AI 搜索 调用外部服务 GitHub 仓库 651.4 万 Codex、Claude、Cursor 有
Azure Cloud migrate 部署 调用外部服务 GitHub 仓库 650.7 万 Codex、Claude、Cursor 有

SKILL.md 全文

10.0 KB
模型实际读到的说明书原文,来自技能仓库

Shadow Agent — Fleet Monitoring & Intervention

Overview

A deterministic background agent that monitors all agents in the fleet via scheduled
heartbeat checks. Shadow Agents run silently, observe everything, and intervene only
when explicitly commanded or when critical anomalies are detected.

Architecture

┌─────────────────────────────────────────────────────────────────┐
│                     Shadow Agent                                 │
│  ┌──────────────┐  ┌──────────────┐  ┌──────────────────────┐ │
│  │ Heartbeat    │  │ FleetBus     │  │ Mailbox Monitor      │ │
│  │ Scheduler    │  │ Subscriber   │  │ (read/query/broadcast)│ │
│  │ (cron)       │  │             │  │                      │ │
│  └──────┬───────┘  └──────┬───────┘  └──────────┬───────────┘ │
│         │                  │                     │              │
│         └──────────────────┼─────────────────────┘              │
│                            ▼                                    │
│                   ┌─────────────────┐                          │
│                   │ LLM Analyzer    │ ← model: configured-model  │
│                   │ (pattern detect)│   setmodel to change       │
│                   └────────┬────────┘                          │
│                            │                                   │
│         ┌─────────────────┼─────────────────┐                │
│         ▼                 ▼                 ▼                │
│  ┌────────────┐   ┌──────────────┐   ┌──────────────┐        │
│  │ Intervention│   │ Report       │   │ Spike        │        │
│  │ Handler    │   │ Generator    │   │ Detector     │        │
│  │ (hoop/etc) │   │ (status)    │   │ (burst tasks)│        │
│  └────────────┘   └──────────────┘   └──────────────┘        │
└─────────────────────────────────────────────────────────────────┘
                            │
                            ▼
              ┌─────────────────────────────┐
              │ FleetBus + Mailbox + Cron    │
              │ (cross-terminal visibility) │
              └─────────────────────────────┘

Core Responsibilities

1. Fleet Monitoring (every 30s by default)

  • Subscribe to FleetBus for all subagent lifecycle events
  • Call fleet (action: status) + fleet (action: health) on each heartbeat
  • Track what each agent is currently doing (via task descriptions)
  • Detect stuck agents (>5 min no events), idle agents, crashed agents

2. Mailbox Surveillance

  • Monitor all mailbox messages (broadcast + direct)
  • Track message patterns: who is talking to whom, frequency
  • Detect orphan tasks (assign without result), stale asks
  • Cross-session awareness: see agents from other terminals

3. Spike Detection

  • Track task duration per agent type
  • Detect instant start/stop patterns (spike tasks)
  • Flag agents that spawn and die within seconds
  • Report efficiency anomalies

4. Deterministic Scheduling

  • Uses cron_schedule for fixed-interval heartbeats
  • Configurable interval: shadow_interval_ms (default 30000)
  • No randomness — same state always produces same actions
  • Clean startup/shutdown via cron cancel on teardown

5. LLM Analysis

  • Uses the configured model without a built-in model default
  • setmodel <model-id> changes the analysis model
  • Prompt-engineered for pattern detection
  • Minimal token usage — snapshot analysis only

6. Intervention Commands

Commands received via mailbox or direct invocation:

Command Action
hoop <subagentId> Immediate terminate via terminate_subagent
hoop all Terminate all running subagents
shadow status Report current fleet snapshot
shadow mute Pause heartbeat monitoring
shadow resume Resume heartbeat monitoring
shadow interval <ms> Change heartbeat interval
shadow intervene <task> Assign a custom intervention task

Data Structures

ShadowState (persisted)

interface ShadowState {
  enabled: boolean;
  intervalMs: number;
  model: string;
  startTime: string; // ISO8601
  lastHeartbeat: string; // ISO8601
  knownAgents: Map<agentId, AgentSnapshot>;
  spikeHistory: SpikeEvent[];
  anomalyLog: Anomaly[];
}

AgentSnapshot

interface AgentSnapshot {
  agentId: string;
  sessionId: string;
  name: string;
  role: string;
  status: 'running' | 'idle' | 'stopped' | 'unknown';
  currentTask?: string;
  lastSeen: string;
  eventCount: number;
  startedAt: string;
}

SpikeEvent

interface SpikeEvent {
  agentId: string;
  spawnedAt: string;
  terminatedAt: string;
  durationMs: number;
  task?: string;
  reason?: string; // 'completed' | 'error' | 'killed' | 'timeout'
}

Anomaly

interface Anomaly {
  id: string;
  type: 'stuck_agent' | 'spike_task' | 'mailbox_loop' | 'budget_exhausted';
  severity: 'low' | 'medium' | 'high' | 'critical';
  agentId?: string;
  description: string;
  detectedAt: string;
  resolvedAt?: string;
}

Output Format

Status Report

## Shadow Agent Status — <timestamp>

**Fleet**: <N> agents tracked | <M> running | <K> idle | <L> stopped
**Heartbeat**: every <X>s | Last: <timestamp>
**Model**: <model-id>

### Active Agents
| Agent | Session | Role | Status | Task | Last Seen |
|-------|---------|------|--------|------|-----------|
| ... | ... | ... | ... | ... | ... |

### Recent Anomalies
- [HIGH] agent-xyz stuck for 5m — no events detected
- [MED] Spike: agent-abc ran for 3s then died

### Mailbox Summary
- Unread: <N> messages | Broadcasts: <M>
- Pending asks: <K> (oldest: <agent> <age>)

Intervention Log

## Shadow Intervention Log

| Time | Command | Target | Result |
|------|---------|--------|--------|
| 10:23:01 | hoop | subagent-xyz | terminated |
| 10:25:33 | hoop | all | 3 agents terminated |

Workflow

Startup

  1. Read persisted ShadowState (if exists)
  2. Subscribe to FleetBus (onAny handler for all events)
  3. Schedule heartbeat cron job at configured interval
  4. Send broadcast: shadow:started { intervalMs, model, startTime }

Heartbeat (every intervalMs)

  1. Call fleet (action: status) + fleet (action: health)
  2. Compare against known agents — detect changes
  3. For each new agent: record snapshot, log "agent joined"
  4. For each missing agent: mark unknown, log "agent left"
  5. Analyze for anomalies (stuck, spike, loop)
  6. If anomaly detected AND auto_intervene enabled: act
  7. If anomaly detected AND auto_intervene disabled: report only
  8. Update ShadowState.lastHeartbeat

FleetBus Events

subagent.started  → record agent, log
subagent.stopped   → record termination, check for spike
subagent.error     → log error, flag anomaly
tool.executed      → increment eventCount for agent
task.assigned      → update currentTask for agent
task.completed     → clear currentTask, log duration

Mailbox Monitoring

On incoming message:
  - If type=control and body starts with "hoop": execute intervention
  - If type=ask with subject "shadow status": send full report
  - If type=broadcast: track in mailbox summary
  - If type=assign without result within 5min: flag orphan

Intervention (hoop)

  1. Parse target (single agent, "all", or pattern)
  2. Call terminate_subagent(target) for each
  3. Log intervention with timestamp
  4. Send result to mailbox (to=sender)
  5. If target="all": also cancel all pending cron jobs

Configuration

Config Key Type Default Description
shadow_interval_ms number 30000 Heartbeat interval in ms
shadow_model string session model Analysis model
shadow_auto_intervene boolean false Auto-act on anomalies
shadow_stuck_threshold_ms number 300000 5min = stuck agent
shadow_spike_threshold_ms number 5000 5s = spike task

Skills in scope

  • fleet-management — uses fleet (action: status), fleet (action: health), terminate_subagent
  • mailbox — uses mailbox tools for monitoring and intervention
  • cron — uses cron_schedule for deterministic heartbeats
  • multi-agent — for spawning analysis subagents when needed
  • observability — for structured logging of anomalies

Anti-Patterns

  • No randomness: Deterministic — same input → same output
  • No blocking: Heartbeats are async, never block agent loop
  • No loud logging: Uses DEBUG level unless anomaly
  • No direct tool calls: Uses FleetBus subscription, not polling
  • Minimal footprint: Shadow state is small, persisted efficiently

常见问题

5 问
答案由本站依据条目字段整理
Shadow Agent怎么安装?

没有现成安装命令:按安装说明或仓库 README,把 SKILL.md 放进客户端的 skills 目录(一般一个技能一个文件夹)。

Shadow Agent支持哪些客户端?

资料没有标注宿主客户端,但只要客户端支持 Skills(Claude、Codex、Cursor 等),一般都能加载。

Shadow Agent权限高吗,安全吗?

权限级别为未标注权限。安装前先看它会读取或写入哪些内容。

Shadow Agent收费吗?

本站不代收费用,也没有标注具体价格。是否收费取决于技能本身和所用的模型或客户端,正式使用前按作者说明确认。

Shadow Agent用什么许可证?

许可证标注为 未说明(许可证不明确)。商用或二次分发前请到仓库确认条款原文。

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技能内容以作者仓库为准;分类、权限级别与许可证状态的中文说明为中文整理,最近核验 未标注。