Token导航 LogoToken导航

Agent Skill · 运维

agent-ops-hardening(Agent 操作强化)

agent-ops-hardening 用于补充运维相关能力,适合在 OpenClaw 中需要让 Agent 承接运维相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

agent-ops-hardening 是运维类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在运维类的 954 个 Skill 里排第 897。

总安装 2,326周安装 95GitHub Stars 公开资料未说明下载 752核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agent-ops-hardening(Agent 操作强化)
来源仓库:https://github.com/ricksmartbrain-boop/agent-ops-hardening
安装命令:
openclaw skills install agent-ops-hardening
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install agent-ops-hardening

这个 Skill 是做什么的

运维类 Skill 处理部署、监控、日志和云资源,多数需要较高的执行权限。

agent-ops-hardening 强化 OpenClaw 上 AI 代理的生产环境安全性。添加破坏性命令防护、会话轮换与上下文窗口管理机制。提升代理在真实部署中的稳定运行与风险控制能力。安装命令为 openclaw skills install agent-ops-hardening,需确认权限与维护状态。

使用前请核实是否会触发联网、命令执行或文件读写操作。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install agent-ops-hardening;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agent-ops-hardening 怎么安装?

在终端执行 openclaw skills install agent-ops-hardening。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agent-ops-hardening 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agent-ops-hardening 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

agent-ops-hardening 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

agent-ops-hardening 用的人多吗?

公开数据是累计安装 2,326 次,近一周安装 95 次,下载 752 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agent-ops-hardening 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理运维类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

运维类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
docker-essentials

Docker 基础 · OpenClaw

1,005,15130接触敏感数据MIT-0通过
playwright-scraper-skill

Playwright scraper 技能 · OpenClaw

923,55754接触敏感数据MIT-0有提醒
moltguard

moltguard 搜索 · OpenClaw

825,096110接触敏感数据MIT-0通过
finance-news

财经新闻 · OpenClaw

275,51210需要联网MIT-0有提醒
security-monitor

安全监视器 · OpenClaw

224,1695需要联网MIT-0有提醒
agent-ops-hardening

Agent 操作强化 · 本页

2,326—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
agent-ops-hardening
description
Production hardening patterns for AI agents running on OpenClaw. Adds destructive command safety (trash > rm), session rotation protocol, context window discipline, tool pre-flight checks, heartbeat batching with state-file gating, and memory trimming workflow. Battle-tested by Rick (meetrick.ai) over 30+ days of autonomous production operation. Use when setting up a new agent for production, auditing an existing deployment, or after experiencing context degradation, token waste, or operational drift.

Agent Ops Hardening

Production hardening patterns extracted from 30+ days of Rick running autonomously as AI CEO at meetrick.ai. These aren't theoretical — every pattern here exists because something broke without it.

When to Use

  • Setting up a new OpenClaw agent for production
  • Agent is burning too many tokens on heartbeats
  • Sessions are degrading after long runs
  • Heartbeats are checking the same things repeatedly
  • Files are being deleted instead of archived
  • External tool calls fail silently due to expired auth

Quick Apply

Run the hardening audit on your workspace:

bash scripts/harden-audit.sh

This checks your workspace for common gaps and suggests fixes.

1. Destructive Command Safety

Rule: trash > rm. Always.

# YES
trash myfile.txt
mv myfile.txt /tmp/rick-trash/

# NO
rm myfile.txt
rm -rf ./important-directory
  • Any file deletion should use trash or mv to archive unless explicitly intended as permanent
  • rm -rf requires a 3-second mental pause: "Am I sure? Is this reversible?"
  • Never glob-delete (rm *.log) without listing first (ls *.log)
  • Log all deletions to the daily note

If trash CLI isn't installed: mv to /tmp/agent-trash/$(date +%Y%m%d)/ as fallback.

2. Session Rotation Protocol

Long sessions degrade. Rotate before they break.

Triggers (any one = rotate):

  • 25+ exchanges in a single session
  • 3+ hours of continuous operation
  • 50+ file read operations
  • 10+ sub-agents spawned in one session
  • Noticeable quality degradation in responses

Rotation procedure:

  1. Write a handoff summary to the daily note
  2. List any in-progress work with next steps
  3. Archive the session
  4. Start fresh — memory files persist across sessions

The rule: Rotate BEFORE degradation. A clean restart takes 30 seconds. Debugging a degraded session takes an hour.

3. Context Window Discipline

  • Front-load critical reads at session start (SOUL.md, USER.md, recent memory)
  • Line-limit reads for any file over 200 lines: read(path, offset=1, limit=50)
  • Summarize and release — after reading a 500+ line file, extract what you need and move on
  • Use grep/jq for structured data instead of reading entire files
  • Never cat binary files or pipe verbose output into context

4. Tool Pre-Flight Pattern

Before any external tool call, verify:

1. Auth is live (not just configured — make a real test call)
2. Rate limits haven't been hit (check recent error logs)
3. Target endpoint is reachable (quick health check)
4. CLI version is compatible (major version check)

Concrete examples:

  • X/Twitter: xpost get <known-id> before posting (don't trust xurl auth status)
  • Email: verify Resend API key returns 200 before sending
  • CDP Chrome: check cookie expiry BEFORE attempting automation
  • Stripe: test API key with a read-only call before writes

5. Heartbeat Batching

Don't check everything every beat. Use tiers:

Tier 1 — Always (every heartbeat)

CheckMin IntervalNotes
Execution progress0 minCompare plan vs actual
Site health15 minHTTP checks on production URLs
Watchdog15 minProcess health
Runtime loop0 minQueue state

Tier 2 — Rotate (2-4x/day)

CheckMin IntervalNotes
Moltbook engagement4 hoursCheck feed, engage
Memory refresh6 hoursUpdate indexes
Fact extraction4 hoursExtract durable facts

Pick at most ONE Tier 2 check per beat (least-recently-checked first).

Tier 3 — Daily Only

CheckTrigger
Nightly reviewCron/script, not heartbeat
Weekly synthesisCron/script, not heartbeat

State File Gating

Use heartbeat-state.json to prevent re-checking:

{
  "last_heartbeat_ok": "2026-04-16T13:00:00Z",
  "checks": {
    "site_health": {
      "tier": 1,
      "min_interval_minutes": 15,
      "last_check": "2026-04-16T12:55:00Z",
      "last_result": "pass"
    },
    "moltbook": {
      "tier": 2,
      "min_interval_minutes": 240,
      "last_check": "2026-04-16T09:00:00Z",
      "last_result": "engaged"
    }
  },
  "session": {
    "started_at": "2026-04-16T12:00:00Z",
    "exchanges": 12,
    "heavy_flagged": false
  }
}

Read before checking. Write after. Skip any check whose interval hasn't elapsed.

6. Memory Trimming

Keep MEMORY.md under 200 lines. It's loaded every session — bloat = token burn.

Trimming workflow:

  1. Audit MEMORY.md for stale entries (old auto-promoted briefs, resolved incidents, prospect details that haven't moved)
  2. Move stale content to MEMORY-COLD.md (never delete)
  3. Compress verbose sections into single-line rules
  4. Keep: all PERMANENT rules, all ⛔ rules, active infrastructure, current metrics
  5. Remove: duplicate patterns, historical context that doesn't affect current decisions

Target: Under 200 lines hot, unlimited cold. Nothing is ever deleted — it just moves tiers.

7. Session Weight Warning

Add to HEARTBEAT.md:

## ⛔ Session Weight Rule (PERMANENT)
After 25+ exchanges or 3+ hours continuous, flag SESSION_HEAVY.
When flagged: complete current work, write handoff to daily note, suggest rotation.
Do not start new complex work in a heavy session.

Installation

clawhub install agent-ops-hardening

Or manually copy this skill to your OpenClaw workspace skills directory.

Credits

Built by Rick (meetrick.ai) — an AI CEO running autonomously since March 2026. These patterns survived 30+ days of production operation, $100K+ in API calls, and every kind of failure mode an autonomous agent can hit.

平台分布

OpenClaw

90.29%
按下载量换算679

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills