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研究检索external-servicegithub未标认证来源可访问许可证需确认审计提醒

conduktorconduktor 搜索

Agent Skill

conduktor 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。

总安装

998

周安装

42

GitHub Stars

5

下载量

349
CodexClaudeCursorGemini CLI

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

unknown

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:conduktor(conduktor 搜索)
来源仓库:https://github.com/conduktor/skills
仓库路径:skills/conduktor
安装命令:
npx skills add https://github.com/conduktor/skills --skill conduktor
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/conduktor/skills --skill conduktor

简介

围绕 Apache Kafka 提供三大核心产品:Console 观测集群、Gateway 透明代理、CLI 管理工具。

  • 支持 RBAC、主题目录、监控、字段级加密与流量控制等企业级特性。
  • 适用于 Kafka 运维、安全与自助服务场景,提升数据治理能力。
  • 需配合 PostgreSQL 数据库部署 Console,Gateway 需客户端重定向至代理端口。
  • conduktor 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Conduktor Platform

Conduktor is three products that work together around Apache Kafka:

  • Console (conduktor/conduktor-console, port 8080) observes and manages Kafka clusters. It provides RBAC, a topic catalog, monitoring, a self-service framework, and data quality policies. Requires PostgreSQL.
  • Gateway (conduktor/conduktor-gateway, port 6969) is a transparent Kafka proxy that intercepts and modifies requests and responses. It provides interceptors, virtual clusters, field-level encryption, data masking, and traffic control. Clients connect to Gateway instead of Kafka directly.
  • CLI (conduktor binary) is a kubectl-style tool that manages both Console and Gateway resources declaratively via YAML apply/get/delete.

Console and Gateway are separate services. Console can manage Gateway, but they deploy independently.

Always read first

For any Conduktor question, load references/mental-model.md to understand product boundaries, the Gateway resource model, virtual clusters, and the self-service framework.

For things AI assistants commonly get wrong, see references/anti-patterns.md.

For Conduktor-to-Kafka terminology mapping, see references/terminology.md.

Use cases

Platform engineer

I want to...Read
Deploy Console and Gateway (Docker, Helm, Kubernetes)use-cases/platform/deploy-conduktor.md
Encrypt or mask Kafka data (field-level, payload)use-cases/platform/encrypt-kafka-data.md
Enforce data quality rules (CEL, JSON Schema)use-cases/platform/enforce-data-quality.md
Set up multi-tenancy (virtual clusters, ACLs, service accounts)use-cases/platform/multi-tenancy.md
Apply traffic control and safeguards (rate limits, topic policies)use-cases/platform/traffic-control.md
Automate with CLI and GitOps (apply, CI/CD, state management)use-cases/platform/gitops-automation.md
Set up self-service GitHub CI/CD (workflows, CODEOWNERS, tokens, policies)use-cases/platform/self-service-github-cicd-cli.md
Bootstrap self-service from existing clusters, topics, and permissionsuse-cases/platform/bootstrap-self-service-cli.md
Manage infrastructure as code with Terraformuse-cases/platform/terraform.md

Application developer

I want to...Read
Get started with Kafka through Conduktor (connect, discover topics)use-cases/app-developer/onboard-to-kafka.md
Create a topic through self-serviceuse-cases/app-developer/create-topic.md
Produce and consume through Gateway (client configs, schemas)use-cases/app-developer/produce-consume.md
Request access to another team's topicuse-cases/app-developer/request-access.md

Agent behavior

IMPORTANT: Do NOT call any documentation MCP tool before completing steps 1-2 below. These skill files + CLI discovery contain everything you need. MCP docs are a last resort (step 5).

When a user asks about Conduktor, do not just explain how things work. Be an active assistant:

  1. Discover first with CLI — read the matching use-case file, then run the exact conduktor get commands from its "Agent workflow" section. The CLI gives you real state; docs give you generic examples.
  2. Ask with options — use discovery results to offer concrete choices instead of open-ended questions. If an AskUserQuestion tool is available, use it with predefined options (e.g. topic name suggestions, partition counts, retention presets). Ask one question at a time, not a list of numbered questions. Prefer sensible defaults — only ask when the choice genuinely matters.
  3. Generate ready-to-use output — produce complete YAML, HCL, or client configs with real names from discovery. Never give templates with placeholders when you can fill in real values.
  4. Execute with confirmation — offer to run conduktor apply -f --dry-run first, then conduktor apply -f on approval. For Terraform, offer terraform plan then terraform apply.
  5. Look up what you don't know — only after checking skill files AND CLI discovery, if the answer is still missing, check your available tools for a search_conduktor_documentation tool (Conduktor's MCP docs server). This is a fallback, not a first step. Never invent env var names, config fields, or API endpoints that are not in these files. If the MCP tool is not available, tell the user to add it with this config: {"mcpServers": {"conduktor-docs": {"type": "url", "url": "https://docs.conduktor.io/mcp"}}}

The CLI requires auth. If commands fail with 401/connection errors, help the user configure CDK_BASE_URL + CDK_API_KEY (Console) or CDK_GATEWAY_BASE_URL + CDK_GATEWAY_USER/CDK_GATEWAY_PASSWORD (Gateway).

Intent routing

When a user mentions these keywords, load the corresponding file:

  • encrypt, mask, PII, GDPR, shield -> use-cases/platform/encrypt-kafka-data.md
  • data quality, CEL, validate, enforce schema -> use-cases/platform/enforce-data-quality.md
  • virtual cluster, tenant, isolation, team namespace -> use-cases/platform/multi-tenancy.md
  • rate limit, throttle, safeguard, quota, traffic -> use-cases/platform/traffic-control.md
  • deploy, Docker, Helm, Kubernetes, install -> use-cases/platform/deploy-conduktor.md
  • conduktor CLI, apply, GitOps, CI/CD, pipeline, automation -> use-cases/platform/gitops-automation.md
  • GitHub Actions, CODEOWNERS, workflow, token scope, ResourcePolicy examples, onboarding app -> use-cases/platform/self-service-github-cicd-cli.md
  • bootstrap, self-service, adopt, migrate, ownership, reverse-engineer -> use-cases/platform/bootstrap-self-service-cli.md
  • Terraform, IaC, HCL, provider -> use-cases/platform/terraform.md
  • onboard, connect, credentials, getting started, bootstrap -> use-cases/app-developer/onboard-to-kafka.md
  • create topic, new topic, self-service topic -> use-cases/app-developer/create-topic.md
  • produce, consume, schema registry, consumer group -> use-cases/app-developer/produce-consume.md
  • access, permission, request, share topic -> use-cases/app-developer/request-access.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

36.49%
按下载量换算127

Claude

29.94%
按下载量换算104

Cursor

20.18%
按下载量换算70

Gemini CLI

9.91%
按下载量换算35

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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