Token导航 LogoToken导航

Agent Skill · 研究检索

google-cloud-recipe-networking-observability(Google cloud recipe networking observability 搜索)

google-cloud-recipe-networking-observability 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

google-cloud-recipe-networking-observability 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 4,504。

总安装 31,824周安装 1,290GitHub Stars 5,709下载 10,192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
unknown

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:google-cloud-recipe-networking-observability(Google cloud recipe networking observability 搜索)
来源仓库:https://github.com/google/skills
仓库路径:skills/google-cloud-recipe-networking-observability
安装命令:
npx skills add https://github.com/google/skills --skill google-cloud-recipe-networking-observability
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/google/skills --skill google-cloud-recipe-networking-observability

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

google-cloud-recipe-networking-observability 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于关键词搜索、任务场景匹配或来源线索梳理等研究检索需求。

通过 npx skills add 命令从指定 GitHub 仓库安装并使用。安装前需确认权限范围、维护状态,以及是否会触发联网或文件操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/google-cloud-recipe-networking-observability

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/google/skills --skill google-cloud-recipe-netw…;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

    它需要执行命令,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

google-cloud-recipe-networking-observability 怎么安装?

在终端执行 npx skills add https://github.com/google/skills --skill google-cloud-recipe-networking-obs…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

google-cloud-recipe-networking-observability 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

google-cloud-recipe-networking-observability 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/google/skills --skill google-cloud-recipe-networking-observability 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

google-cloud-recipe-networking-observability 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

google-cloud-recipe-networking-observability 用的人多吗?

公开数据是累计安装 31,824 次,近一周安装 1,290 次,下载 10,192 次,GitHub 5,709 星。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。

google-cloud-recipe-networking-observability 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 5,709 星,维护活跃度相对可查。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
google-cloud-recipe-networking-observability

Google cloud recipe networking observability 搜索 · 本页

31,8245,709执行命令未明确通过

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

Google Cloud Networking Observability Expert

🛑 Core Directive: Results First

  1. Identify the Primary Source: Quickly determine if the user needs firewall logs, threat logs, Cloud NAT, VPC Flow logs, or metrics.
  2. Execute & Present: Perform the minimum required query to get a direct answer.
  3. Definitive Termination: Once you identify the requested data, regardless of the value (including 0, null, or "No traffic"), present the finding and call the finish tool in the same turn. Do NOT attempt to find "active" or "busier" resources to provide a "better" answer unless specifically instructed to troubleshoot a resource that is expected to be busy.

Log & Telemetry Overview

  • Threat Logs: Specialized logs from Cloud Firewall Plus and Cloud IDS that identify malicious traffic patterns (for example, SQL injection or malware) using deep packet inspection.
  • VPC Flow Logs: Capture sample IP traffic to and from network interfaces. Use for traffic analysis, volume trends, and top talkers.
  • Firewall Logs: Record connection attempts matched by firewall rules. Use to identify "DENY" events or verify "ALLOW" rules.
  • Cloud NAT Logs: Audit NAT translations. Use to audit traffic going through NAT gateways or troubleshoot port exhaustion.
  • Networking Metrics: Aggregated time-series data for throughput, RTT (latency), and packet loss. Use for historical trends and performance monitoring.
  • Connectivity Tests: Static analysis tool for path diagnostics. Use to identify firewall or routing misconfigurations between endpoints.

Procedures

0. Log Source Preference

  • ALWAYS check for BigQuery linked datasets (for example, big_query_linked_dataset, _AllLogs) before using Cloud Logging for high-volume analysis or aggregations. This is the preferred method for finding trends or top-blocking rules.
  • Metadata Awareness (BigQuery): Subnetworks may be configured with EXCLUDE_ALL_METADATA, causing VM names to be NULL in VPC Flow Logs. If a query by VM name returns nothing, retry using the internal IP address (jsonPayload.connection.src_ip).

1. Tool Selection & Discovery

1. Use run_shell_command with gcloud to list resources in the project. 2. Search Cloud Logging MCP for the resource name to find correct labels.

  • CLI Fallback: Use gcloud or bq only if MCP servers are unavailable. DO NOT use gcloud monitoring; it is restricted. Immediately use the curl templates in metrics-analysis.md.

2. Schema Verification & Error Recovery

If a BigQuery query fails with an 'Unrecognized name' error or schema mismatch:

  1. Validate Schema: Run bq show --schema --format=json {project_id}:{dataset_id}.{table_id} to verify field names and casing (for example, jsonPayload versus json_payload). 2. Dry Run: Before executing a corrected query, use bq query --use_legacy_sql=false --dry_run "{query_text}" to verify field references without incurring cost or execution time. 3. Retry: Apply identified fixes to the original query and execute.

3. Analysis Guides (Read Only When Needed)

For detailed SQL patterns, field definitions, and advanced troubleshooting, read the corresponding reference file:

Boundaries (CRITICAL)

  • ALWAYS present the direct answer as soon as it is identified.
  • NEVER run more than 2 exploratory queries before showing results.
  • NEVER perform secondary verification (for example, don't check VPC flows after finding a firewall block) without explicit user permission.
  • ALWAYS print the generated SQL for review before execution.
  • ALWAYS include a link to the Flow Analyzer in the Google Cloud Console.
  • NEVER query a second data source (such as, BigQuery logs) if the primary source (for example, Cloud Monitoring metrics) has already provided a conclusive answer. DO NOT compare metrics and logs to "verify" accuracy unless the user specifically asks why they differ.
  • NO DISCREPANCY LOOPS: If Tool A provides a result (such as, 80,000 counts) and Tool B provides a different result (for example, 1,000 counts), DO NOT initiate a deep dive to explain the difference. Present the result from the primary tool and STOP.
  • ALWAYS perform time-range calculations (such as, "12 hours ago") during the first turn to save steps.
  • Conclusive Acceptance of Inactivity: Treat a result of "0", "0 traffic", "No data found", or "No records found" as a conclusive finding for the requested timeframe and resource. You MUST report this as the definitive state and terminate immediately.
  • Standardized Discovery Path: For all "Top-N" or volume-based discovery tasks (for example, "highest traffic," "most hits," "top talkers"), you MUST use BigQuery aggregation on _AllLogs datasets. Manual aggregation of individual time-series points using the Monitoring API is forbidden due to step inefficiency.
  • Ban on Auxiliary Scripting: Execute all data retrieval and parsing logic as direct tool calls (bq, curl, gcloud). Do NOT write or execute local shell scripts (.sh) or python files, as these introduce avoidable environment and permission errors that lead to investigation timeouts.
  • Discovery Efficiency: For volume analysis (for example, "how many connections" or "top IPs by bytes"), BigQuery aggregation on VPC Flow logs (_AllLogs) is the Primary Source of Truth. If BigQuery data is available, it is conclusive. Do NOT query Monitoring API to "double check" BigQuery counts.

平台分布

Codex

36.16%
按下载量换算3,685

Claude

29.96%
按下载量换算3,054

Cursor

16.73%
按下载量换算1,705

Gemini CLI

8.49%
按下载量换算865

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/google/skills --skill google-cloud-recipe-networking-observability 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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