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server-mate服务器伙伴

Agent Skill

server-mate 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

总安装

5,574

周安装

237

GitHub Stars

1

下载量

1,953
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:server-mate(服务器伙伴)
来源仓库:https://github.com/tankeito/server-mate
安装命令:
openclaw skills install server-mate
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 server-mate

简介

为 Nginx/Apache 主机提供轻量级监控与 AI 操作支持。

  • 收集系统资源使用情况并扩展自动化工作流。server-mate 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 集成 psutil 数据整理,输出 JSON 格式便于下游消费。
  • 需在目标机器安装 Python 环境与必要依赖包。
  • 可与 Prometheus + Grafana 组合搭建可视化面板。

SKILL.md

name
server-mate
version
1.3.3
description
Build or extend a lightweight server monitoring and AI operations workflow for Linux hosts running Nginx or Apache. Use when Codex needs to collect psutil metrics, parse access, error, or auth logs, design JSON payloads or APIs, add webhook alerts, generate PDF ops reports with SSL expiry summaries, answer natural-language monitoring questions, or implement guarded auto-ban and auto-heal behaviors.
homepage
https://github.com/tankeito/server-mate
metadata
clawdbot
files

Server Mate

Version: 1.3.3

Use this skill to design or implement a two-plane monitoring system:

  • a Python agent on the server that tails logs and samples host metrics
  • an OpenClaw-side analyzer that aggregates data, explains failures, answers questions, and sends alerts

Start

  • Confirm the environment first: Linux distribution, Nginx or Apache, PHP-FPM layout, log paths, webhook target, and whether automated actions may touch a live host.
  • Keep collection read-only until the user explicitly asks for automation. Add alerting before any auto-ban or auto-heal behavior.
  • In OpenClaw deployments, OPENAI_API_KEY is injected by the runtime when AI analysis is enabled. Do not ask the user to export it manually. Treat webhook URLs or tokens in config.yaml as secrets and do not commit them.
  • Treat ./data/GeoIP.conf the same way. It may contain MaxMind AccountID and LicenseKey, so keep it local-only and out of Git.
  • Prefer MaxMind's official GeoLite2 workflow through ./data/GeoIP.conf and geoipupdate. Treat the built-in public mirror fallback only as an operator-reviewed bootstrap path when no local .mmdb file is present.
  • Treat auto-ban and auto-heal as privileged features. They may execute operator-supplied firewall or service restart commands and should stay disabled or dry_run: true until reviewed.
  • Use the references progressively instead of loading everything at once:

- Read references/architecture.md for overall design, component boundaries, and rollout order. - Read references/data-contracts.md before defining JSON payloads, storage schemas, metrics, or natural-language query handlers. - Read references/ops-playbook.md before implementing thresholds, webhooks, reports, auto-ban, or self-heal logic. - Read references/sqlite-schema.md before extending historical storage or report queries. - Use scripts/server_agent.py as the collector, daemon entrypoint, and SQLite rollup writer.

Delivery workflow

  1. Map the request to one or more tracks.

- Agent collection - Aggregation and storage - Alerting and reporting - AI diagnosis - Guarded remediation

  1. Implement the smallest safe slice first.

- Start with structured access, error, and system events. - Add rollup metrics and natural-language answers next. - Add webhook alerts after the counters are stable. - Enable auto-ban or auto-heal only when thresholds, cooldowns, allowlists, and audit logs already exist.

  1. Validate with real or synthetic logs before changing production services.
  2. Explain caveats in plain language.

- Example: UV is often an approximation based on IP and user-agent unless the site provides a stronger visitor key. - Example: upload bandwidth is unavailable unless the access log includes request length or a similar field.

Agent rules

  • Prefer Python, psutil, and the standard library for the first implementation.
  • Prefer a generated ./config.yaml plus local SQLite state such as ./metrics.db before adding external services.
  • Keep generated artifacts inside the current skill workspace by default: ./config.yaml, ./metrics.db, ./logs/, and ./reports/. Do not default to /opt, /var/log, or other system-wide directories.
  • Prefer the system_metrics + sites[] matrix layout from config.example.yaml instead of new single-site keys.
  • Support configurable log paths. Do not hardcode site layouts when the vhost config can be read instead.
  • Emit structured JSON with timezone-aware timestamps, host or site identifiers, event type, and enough raw context to debug parser mistakes.
  • In multi-site mode, collect host CPU or memory metrics once per cycle and keep site log parsing isolated per domain.
  • Separate parsing, aggregation, transport, and action execution so that HTTP push, stdout replay, file drop, or websocket transport can be swapped independently.
  • Keep unknown lines and parser failures as first-class counters instead of dropping them silently.

Analyzer rules

  • Store raw events separately from derived counters.
  • Model traffic, performance, security, spider, and error signals as independent reducers over the same event stream.
  • Translate natural-language requests into:

- a time window - filters - an aggregation - a presentation format

  • For AI error explanations, pass the fingerprint, surrounding context, and normalized fields instead of dumping entire logs.

Safety rules

  • Treat auto-ban and auto-heal as opt-in features.
  • Default Guarded Automation to dry_run: true and keep it there until the user has observed automation notifications and audit history for several days.
  • Never flip dry_run to false, or enable auto_ban.enabled / auto_heal.enabled, unless the operator explicitly approves the command templates, allowlists, cooldowns, and audit destinations.
  • Require cooldowns, max actions per window, and allowlists before running firewall or restart commands.
  • Require whitelist checks before any ban command. Never ban loopback, RFC1918 private ranges, or trusted crawler families by default.
  • Require TTL-based unban or an equivalent release plan for every ban. Do not create permanent firewall blocks from the first implementation.
  • Record an audit event for every alert, dry-run, ban, unban, restart, and failed remediation attempt.
  • Store audit history in SQLite tables such as automation_actions and banned_ips, and expose simple lookup queries in user-facing docs.
  • Prefer one-shot remediation followed by escalation. Do not loop restarts.

Report expectations

  • Daily report: prior-day PV, UV, IP, request totals, bandwidth, status mix, top errors, and slow endpoints.
  • Weekly report: blocked IP trends, crawler trends, suspicious route clusters, and recurring slow routes.
  • Monthly report: bandwidth peak, disk growth, capacity warning, and remediation summary.

Automation scheduling

Use external scheduling for production unless the user explicitly wants an always-on daemon-only design.

  • Recommended ingestion pattern:

- Run server_agent.py --once every 10 minutes from cron or a systemd timer. - This keeps log parsing incremental, writes SQLite rollups, and avoids duplicate resident processes.

  • For systemd deployments in Clawhub-style packaging:

- Do not rely on bundling a .service file inside the skill package. - Generate a host-local unit with server_agent.py --config ./config.yaml --generate-service, then paste it into /etc/systemd/system/server-mate.service.

  • Recommended report pattern:

- Run report_generator.py as one-shot scheduled jobs. - Daily PDF push at 01:00. - Weekly PDF push every Monday at 01:10. - Monthly PDF push on day 1 at 01:20.

  • In multi-site mode, a single scheduled report_generator.py run should iterate over every configured site unless the user explicitly passes --site.

Release notes for 1.3.2

  • Multi-site matrix config using sites[] plus global system_metrics
  • Host-global metrics stored separately from site-local business rollups
  • Logrotate-tolerant incremental readers with inode or truncate recovery
  • Guarded Automation with dry_run, whitelist checks, TTL-based unban, cooldown-based auto-heal, and SQLite audit trail
  • SSH brute-force detection from logs.auth_log with ssh_brute_force alerting and optional linked auto-ban
  • SSL certificate expiry inspection in report generation and webhook summaries
  • Telegram delivery support for alerts and report notices
  • GeoIP official refresh support via local ./data/GeoIP.conf and geoipupdate, with an operator-reviewed public mirror bootstrap fallback
  • config.example.yaml and docs updated for MaxMind GeoLite2 setup in the current workspace

Copyable cron examples:

*/10 * * * * /usr/bin/env bash -lc 'python3 ./scripts/server_agent.py --config ./config.yaml --once >> ./logs/server-mate-agent.log 2>&1'
0 1 * * * /usr/bin/env bash -lc 'python3 ./scripts/report_generator.py --config ./config.yaml pdf --range daily --send >> ./logs/server-mate-report.log 2>&1'
10 1 * * 1 /usr/bin/env bash -lc 'python3 ./scripts/report_generator.py --config ./config.yaml pdf --range weekly --send >> ./logs/server-mate-report.log 2>&1'
20 1 1 * * /usr/bin/env bash -lc 'python3 ./scripts/report_generator.py --config ./config.yaml pdf --range monthly --send >> ./logs/server-mate-report.log 2>&1'

Systemd note:

  • If the host already standardizes on systemd, prefer Type=oneshot services plus timers for reports.
  • Use Restart=always only for the long-running --daemon agent mode.

Example requests

  • "Design the ingestion API for Server-Mate."
  • "Add 404 burst detection and webhook alerts."
  • "Explain today's top 5xx error in plain language."
  • "Plan a safe auto-heal flow for repeated 502 responses."

适合场景

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OpenClaw 用户查找和安装 Skill 时

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用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

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需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

87.82%
按下载量换算1,715

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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