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Agent Skill · 开发

openclaw-administrator(OpenClaw administrator 命令行)

openclaw-administrator 用于辅助安全审计、权限检查和凭据风险排查,适合在 OpenClaw 中需要复核安全边界、认证流程或敏感配置时使用。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。

openclaw-administrator 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为操作浏览器;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 9,138。

总安装 2,840周安装 122GitHub Stars 公开资料未说明下载 996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
1.0.2

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:openclaw-administrator(OpenClaw administrator 命令行)
来源仓库:https://github.com/encryptshawn/openclaw-administrator
安装命令:
openclaw skills install openclaw-administrator
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 openclaw-administrator

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

openclaw-administrator 操作与配置 OpenClaw CLI 并进行故障排除。覆盖安装、代理、路由、API、内存、安全等全栈管理。适用于高级配置与多维度诊断任务。安装前需确认权限范围、维护状态及是否会触发敏感操作。建议结合来源仓库和原始 README 核验命令集与风险提示。

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 openclaw-administrator;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

    它需要操作浏览器,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

openclaw-administrator 怎么安装?

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

openclaw-administrator 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。

openclaw-administrator 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

openclaw-administrator 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。

openclaw-administrator 用的人多吗?

公开数据是累计安装 2,840 次,近一周安装 122 次,下载 996 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。

openclaw-administrator 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

  • 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。
  • 需要处理开发类任务、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

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
openclaw-administrator

OpenClaw administrator 命令行 · 本页

2,840—操作浏览器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
openclaw-administrator
description
Administration guide for the OpenClaw CLI. Use this skill whenever the user asks how to run, configure, or troubleshoot any openclaw command or concept, including: gateway and daemon lifecycle, setup and onboarding (interactive and headless/VPS), multi-agent setup and routing bindings, sub-agent spawning and delegation, workspace and bootstrap file management (AGENTS.md, SOUL.md, IDENTITY.md, USER.md, TOOLS.md), adding and configuring AI model providers, setting primary and fallback models, per-agent model overrides, the model allowlist, local models (Ollama/vLLM/LM Studio), custom providers via models.providers, the OpenAI-compatible HTTP endpoint (Open WebUI, LobeChat, LibreChat integration), channel login and connectivity, messaging, memory and wiki, plugins and skills, MCP servers, cron, tasks, flows, sandbox, browser automation, nodes, security audits, backups, and diagnostics. Also use for global flags (--dev, --profile, --container), command family routing, and any question about how openclaw subcommands work.

🛡️ EMERGENCY SAFETY PROTOCOL

  • NO OVERWRITES: Never use cat, redirection (>), or raw file writes to openclaw.json. Use a validated JSON utility script that loads-modifies-saves.
  • SCHEMA VALIDITY: Before adding new keys (e.g., mcp, tools), verify against official schema. Never guess keys.
  • PRE-BOUNCE VERIFICATION:

1. Validate JSON syntax (python -m json.tool). 2. Run openclaw doctor. 3. If any errors, ABORT the bounce.

  • BACKUP INTEGRITY: Maintain a rotating history of up to 3 validated backups (openclaw.json.bak.1 to .bak.3). After a verified successful bounce, prune any backups older than 24 hours and maintain the most recent 3 verified snapshots.
  • SECRET HYGIENE: Never write credential-like patterns (PAT, TOKEN, KEY) into any workspace file. Before removing any existing configuration that contains keys/credentials, ensure they are secured in the environment (~/.openclaw/credentials/.env) first.
  • EXPLICIT AUTHORIZATION: I must never make changes to the openclaw.json or system configuration without *first* proposing the change, explaining the "Why," and obtaining explicit user permission.
  • EXTERNAL SKILL AUDIT: Never install a skill from ClawHub or any external repository without *first* inspecting the source code. Look specifically for:

- Exfiltration of data/tokens to unknown URLs. - Malicious/damaging system commands (e.g., recursive deletion, system modifications). - Hardcoded or suspicious credential usage. Only proceed with installation once the source has been audited as benign.

Execution Workflow

  1. Clarify the target state. Ask what should change and what must stay untouched.
  2. Select runtime scope first. Default profile unless isolation is explicitly needed:

- openclaw --dev ... → isolated dev state under ~/.openclaw-dev, gateway port 19001. - openclaw --profile <n> ... → isolated state under ~/.openclaw-<n>. - openclaw --container <n> ... → target a named container for execution.

  1. Route to the right command family. Use references/command-map.md for quick routing.
  2. Expand subcommands before risky operations. Run openclaw <family> --help for starred families; confirm flags before executing.
  3. Prefer machine-readable output for automation. Use --json where available; parse and verify.
  4. Verify outcomes explicitly. Check with openclaw status, openclaw health, openclaw doctor, or command-specific follow-up.

Safety Rules

  • Require explicit user confirmation before reset, uninstall, destructive --force flows, or operations that remove stored provider keys.
  • Prefer non-destructive diagnostics first: status, health, doctor, logs, security audit.
  • Keep profile scope consistent across a workflow — never mix --dev and default in the same sequence.
  • For gateway issues, diagnose before restart unless restart is explicitly requested.
  • Keep the OpenAI HTTP endpoint on loopback/tailnet only — never expose to the public internet.

Triage Sequence

For any "OpenClaw not working" incident:

  1. openclaw status
  2. openclaw health
  3. openclaw doctor
  4. openclaw security audit (if config or provider connection settings may be misconfigured)
  5. openclaw backup verify <archive> (if data integrity is suspected)
  6. Check openclaw gateway ..., openclaw channels ..., or openclaw nodes ... based on where failure appears.
  7. Escalate to targeted commands in references/command-map.md.

Architecture Overview

OpenClaw runs as a single Gateway (WebSocket, default 127.0.0.1:18789) that:

  • Owns all messaging surfaces (WhatsApp/Telegram/Discord/Slack/Signal/iMessage/etc.)
  • Hosts one or many agents, each with isolated workspace + auth + session store
  • Exposes a typed WS API for CLI/app/automation clients
  • Optionally serves an OpenAI-compatible HTTP surface at the same port

Clients (CLI, macOS app, web UI) connect over WebSocket. Nodes (macOS/iOS/Android/headless) also connect with role: node. The canvas UI is served at /__openclaw__/canvas/.


Workspace and Bootstrap Files

Each agent has a workspace directory (~/.openclaw/workspace by default) containing markdown files the agent reads on boot:

FilePurpose
AGENTS.mdCore instructions, memory, tool policy
SOUL.mdPersona, tone, boundaries
IDENTITY.mdName, emoji, theme, avatar
USER.mdWho the user is; preferences
TOOLS.mdTool usage notes and policies
HEARTBEAT.mdPeriodic check-in template
BOOT.mdOne-time boot ritual (delete after)
BOOTSTRAP.mdStartup sequence instructions
MEMORY.md + memory/*.mdPersistent memory store
  • Missing files get a placeholder marker injected at session start; execution continues.
  • Size limits: bootstrapMaxChars (default 12 000 chars per file), bootstrapTotalMaxChars (default 60 000 total).
  • openclaw setup --workspace <path> recreates any missing defaults without overwriting existing ones.
  • Keep the workspace in a private git repo for backup and recovery. Never commit ~/.openclaw/ state dirs.
  • If ~/openclaw/ (old path) exists alongside ~/.openclaw/workspace, keep only one active workspace to avoid auth/session drift.

Agent System

Single-Agent Mode (default)

Out of the box: one agent, agentId = main, sessions keyed agent:main:<mainKey>.

Multi-Agent Setup

Each agent is a fully isolated brain:

  • Own workspace (agents.defaults.workspace or per-agent override)
  • Own agentDir (~/.openclaw/agents/<agentId>/agent) — holds auth-profiles.json, model registry, per-agent config
  • Own session store (~/.openclaw/agents/<agentId>/sessions)
  • Never reuse agentDir across agents — causes auth/session collisions.

Creating a new agent:

openclaw agents add coding
openclaw agents add work --workspace ~/.openclaw/workspace-work --non-interactive

Identity setup:

openclaw agents set-identity --agent main --name "OpenClaw" --emoji "🦞" --avatar avatars/oc.png
openclaw agents set-identity --workspace ~/.openclaw/workspace --from-identity   # reads IDENTITY.md

Listing and verifying:

openclaw agents list
openclaw agents list --bindings
openclaw agents bindings --agent work

Routing Bindings

Bindings route inbound messages to the correct agent. Most-specific match wins (priority order):

  1. peer (exact DM/group id)
  2. parentPeer (thread inheritance)
  3. guildId + roles (Discord role routing)
  4. guildId (Discord server)
  5. teamId (Slack workspace)
  6. Explicit accountId for a channel
  7. accountId: "*" (channel-wide fallback, all accounts)
  8. Default agent (agents.list[].default, else first entry, else main)

Managing bindings:

openclaw agents bind --agent work --bind telegram:ops --bind discord:guild-a
openclaw agents unbind --agent work --bind telegram:ops
openclaw agents unbind --agent work --all

Omitting --agent targets the current default. A channel-only binding (no accountId) is auto-upgraded to account-scoped when you later add an explicit accountId for the same channel+agent.

Config example (WhatsApp DM split):

{
  "agents": {
    "list": [
      { "id": "home", "default": true, "workspace": "~/.openclaw/workspace-home" },
      { "id": "work", "workspace": "~/.openclaw/workspace-work" }
    ]
  },
  "bindings": [
    { "agentId": "home", "match": { "channel": "whatsapp", "accountId": "personal" } },
    { "agentId": "work", "match": { "channel": "whatsapp", "accountId": "biz" } }
  ]
}

See references/multi-agent-recipes.md for full Discord, Telegram, and WhatsApp examples.

Sub-Agents

Sub-agents are background agent runs spawned by the main agent to handle tasks in parallel. They run in their own isolated session (agent:<agentId>:subagent:<uuid>), receive only the instructions given to them (not full conversation history), and announce results back to the requester channel when done.

Key characteristics:

  • Depth limit: currently flat (sub-agents cannot spawn their own sub-agents; this restriction is expected to be lifted in a future release)
  • Restricted tool policies relative to the parent
  • Auto-announce on completion (direct delivery first, falls back to queue routing, then exponential backoff)
  • Tracked as background tasks; inspect/control via slash commands

Slash command control:

/subagents          # list all background sub-agent runs
/subagents spawn <agentId> <task> [--model <m>] [--thinking <level>]
/focus <target>     # bind current thread to a sub-agent session
/unfocus            # detach thread binding
/session idle       # inspect/update inactivity auto-unfocus
/session max-age    # control hard session age cap

When to use sub-agents vs sessions_send:

  • Sub-agent (sessions_spawn): need the result now, in this conversation; parallel fan-out.
  • sessions_send: fire-and-forget delegation; the other agent works independently and responds later.

Allowlist config (to let sub-agents target named agents):

{
  "agents": {
    "list": [
      {
        "id": "main",
        "subagents": {
          "allowAgents": ["coding", "research"]
        }
      }
    ]
  }
}

Running an Agent Turn

# Run via gateway (default)
openclaw agent --to +15555550123 --message "Status update" --deliver
openclaw agent --agent ops --message "Summarize logs" --thinking medium
openclaw agent --session-id 1234 --message "Summarize inbox" --json

# Run embedded (local, no gateway)
openclaw agent --agent ops --message "Run locally" --local

# Deliver to a different channel/account
openclaw agent --agent ops --message "Generate report" \
  --deliver --reply-channel slack --reply-to "#reports"

Key flags: --thinking <off|minimal|low|medium|high|xhigh>, --verbose <on|off>, --timeout <seconds>.

Gateway mode falls back to embedded when the gateway request fails; --local forces embedded up front.


OpenAI-Compatible HTTP API

The Gateway can serve an OpenAI-compatible HTTP surface at the same port as WebSocket. Disabled by default.

Enable in ~/.openclaw/openclaw.json:

{
  "gateway": {
    "http": {
      "endpoints": {
        "chatCompletions": { "enabled": true }
      }
    }
  }
}

Endpoints (when enabled):

  • POST /v1/chat/completions
  • GET /v1/models / GET /v1/models/{id}
  • POST /v1/embeddings
  • POST /v1/responses

Model field = agent target:

  • "openclaw" or "openclaw/default" → configured default agent
  • "openclaw/<agentId>" → specific agent (e.g. "openclaw/research")
  • Legacy aliases: "openclaw:<agentId>", "agent:<agentId>"

Optional request headers:

  • x-openclaw-model: <provider/model> — override backend model for the agent
  • x-openclaw-agent-id: <agentId> — compatibility agent override
  • x-openclaw-session-key: <key> — control session routing
  • x-openclaw-message-channel: <channel> — set synthetic ingress channel context

Session behavior: stateless per request by default. If the request includes an OpenAI user string, a stable session key is derived from it so repeated calls share the same agent session.

Note: OpenClaw's gateway token is what any connected client uses to authenticate. Keep this endpoint on loopback or a private network (tailnet/VPN) — don't expose it directly to the public internet.

Examples:

# Non-streaming
curl -sS http://127.0.0.1:18789/v1/chat/completions \
  -H 'Authorization: Bearer YOUR_TOKEN' \
  -H 'Content-Type: application/json' \
  -d '{"model":"openclaw/default","messages":[{"role":"user","content":"hi"}]}'

# Streaming with backend model override
curl -N http://127.0.0.1:18789/v1/chat/completions \
  -H 'Authorization: Bearer YOUR_TOKEN' \
  -H 'Content-Type: application/json' \
  -H 'x-openclaw-model: openai/gpt-4o' \
  -d '{"model":"openclaw/research","stream":true,"messages":[{"role":"user","content":"hi"}]}'

# List agent targets
curl -sS http://127.0.0.1:18789/v1/models \
  -H 'Authorization: Bearer YOUR_TOKEN'

# Embeddings
curl -sS http://127.0.0.1:18789/v1/embeddings \
  -H 'Authorization: Bearer YOUR_TOKEN' \
  -H 'Content-Type: application/json' \
  -H 'x-openclaw-model: openai/text-embedding-3-small' \
  -d '{"model":"openclaw/default","input":["alpha","beta"]}'

Open WebUI quick setup:

  • Base URL: http://127.0.0.1:18789/v1 (Docker on macOS: http://host.docker.internal:18789/v1)
  • API key: your gateway bearer token
  • Model: openclaw/default

Storing provider keys outside the config file (SecretRefs)

OpenClaw supports referencing provider keys via environment variables, files, or exec commands instead of writing plaintext values into openclaw.json. This is an OpenClaw configuration feature — the skill just explains how to set it up.

Reference typeSyntaxExample
Env variablesecretref-env:VAR_NAMEsecretref-env:ANTHROPIC_API_KEY
File pathsecretref-file:/path/to/filesecretref-file:~/.secrets/openai_key
Exec commandsecretref-exec:commandsecretref-exec:op read op://vault/item/field

Set a reference via CLI:

openclaw config set providers.anthropic.key \
  --ref-provider env --ref-source ANTHROPIC_API_KEY

openclaw secrets configure       # interactive setup wizard
openclaw secrets reload          # reload without gateway restart
openclaw secrets audit           # check all references resolve correctly
openclaw secrets audit --check   # non-zero exit on failures (CI use)

Use ref mode during non-interactive onboard:

openclaw onboard --non-interactive \
  --auth-choice anthropic-api-key \
  --secret-input-mode ref \
  --anthropic-api-key secretref-env:ANTHROPIC_API_KEY

Setup and Onboarding

Interactive (recommended for first-time):

openclaw onboard

Non-interactive (VPS/headless):

openclaw onboard \
  --non-interactive \
  --auth-choice anthropic-api-key \
  --anthropic-api-key <key> \
  --gateway-bind loopback \
  --install-daemon \
  --daemon-runtime node \
  --node-manager pnpm \
  --skip-channels \
  --skip-search

Key --auth-choice values: anthropic-api-key, openai-api-key, openrouter-api-key, gemini-api-key, github-copilot, chutes, deepseek-api-key, custom-api-key, skip.

Key gateway bind modes: loopback (default), lan, tailnet, auto.

For Tailscale: --tailscale <off|serve|funnel>. For remote gateway: --mode remote --remote-url <url> --remote-token <token>.


Models and Providers

Read references/models-and-providers.md for the full reference. It covers: model selection order, primary/fallback config, per-agent overrides, the model allowlist, custom providers, local models (Ollama/vLLM/LM Studio), multi-key rotation, how failover and cooldowns work, and sub-agent model config.

Quick orientation:

Model refs use provider/model format: anthropic/claude-opus-4-6, openai/gpt-5.4, ollama/llama3.3.

# Essential commands
openclaw models list                            # see configured models
openclaw models status                          # primary, fallbacks, auth overview
openclaw models set anthropic/claude-opus-4-6  # set primary model
openclaw models set-image openai/gpt-image-1   # set image model
openclaw models fallbacks add openrouter/auto   # add a fallback
openclaw models aliases add Opus anthropic/claude-opus-4-6
openclaw models auth login                      # add/re-auth a provider
openclaw models auth login-github-copilot       # GitHub Copilot device login
openclaw models scan                            # find free models on OpenRouter

Config: primary + fallback chain:

{
  "agents": {
    "defaults": {
      "model": {
        "primary": "anthropic/claude-opus-4-6",
        "fallbacks": [
          "openrouter/anthropic/claude-opus-4-6",
          "openai/gpt-5.4"
        ]
      }
    }
  }
}

Config: add a custom/third-party provider (any OpenAI-compatible API):

{
  "models": {
    "mode": "merge",
    "providers": {
      "my-provider": {
        "baseUrl": "https://api.example.com/v1",
        "apiKey": "${MY_PROVIDER_KEY}",
        "api": "openai-completions",
        "models": [
          { "id": "my-model", "name": "My Model" }
        ]
      }
    }
  }
}

Use api: "anthropic-messages" for Anthropic-compatible endpoints. After adding a provider: openclaw config validate, openclaw models list --provider my-provider, openclaw gateway restart.

Per-agent model (each agent can use a different model):

{
  "agents": {
    "list": [
      { "id": "main", "model": "anthropic/claude-opus-4-6" },
      { "id": "fast", "model": "anthropic/claude-haiku-4-5" }
    ]
  }
}

For built-in providers (Anthropic, OpenAI, Google, OpenRouter, GitHub Copilot, Mistral, xAI, DeepSeek, Ollama, and 20+ more) and their --auth-choice values, see references/models-and-providers.md.


Inference CLI (infer / capability)

Direct inference without a full agent run:

openclaw infer list                                    # list capabilities
openclaw infer model run --model anthropic/claude-sonnet-4-6 --prompt "hi"
openclaw infer image generate --prompt "a lobster in space"
openclaw infer image describe path/to/image.jpg
openclaw infer audio transcribe recording.mp3
openclaw infer tts convert --text "Hello" --voice nova
openclaw infer web search "latest OpenClaw release"
openclaw infer web fetch https://example.com
openclaw infer embedding create --input "embed this text"

Channels

openclaw channels list
openclaw channels status --probe            # live per-account probe
openclaw channels add --channel telegram --account alerts --token $TOKEN
openclaw channels add --channel discord --account work --token $DISCORD_TOKEN
openclaw channels remove --channel discord --account work --delete
openclaw channels login --channel whatsapp --account personal --verbose
openclaw channels logout --channel whatsapp --account personal
openclaw channels capabilities --channel telegram --account alerts
openclaw channels logs --channel whatsapp --lines 200

Supported channels: whatsapp, telegram, discord, googlechat, slack, signal, imessage, msteams, mattermost (plugin), and many more via plugins.

DM security policies: dmPolicy: "pairing" (unknown senders get a code), dmPolicy: "allowlist" (explicit list only), dmPolicy: "open".


Resources

Read the appropriate reference file before answering deep questions in these areas:

ReferenceWhen to read it
references/command-map.mdFull command tree, routing quick-map, common recipes, caution commands
references/models-and-providers.mdAdding providers, fallback chains, custom config, local models, auth rotation, failover
references/multi-agent-recipes.mdAnnotated multi-agent JSON configs (WhatsApp, Discord, Telegram, channel split)
references/openai-http-api.mdEnabling the HTTP endpoint, model targeting, headers, Open WebUI setup

Live docs: openclaw docs [query] or https://docs.openclaw.ai

平台分布

OpenClaw

71.79%
按下载量换算715

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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。

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