数据库安装
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- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: aiven-kafka-setup-avn
description: > Use when this capability is needed. End-to-end workflow for creating an Apache Kafka service o…
category: 通用
runtime: Python
---
# aiven-kafka-setup-avn 输出预览
## PART A: 任务判断
- 适用问题:通用任务拆解、检查和交付。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Step 1: Prerequisites / 1.1 Verify avn CLI login / 1.2 Required tools”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于通用任务拆解、检查和交付,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Step 1: Prerequisites / 1.1 Verify avn CLI login / 1.2 Required tools”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、执行终端命令、读取环境变量、主要在本地完成、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件、执行终端命令、读取环境变量;主要在本地完成;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件、执行终端命令、读取环境变量。
先用一个小任务确认它会围绕“Step 1: Prerequisites / 1.1 Verify avn CLI login / 1.2 Required tools”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: aiven-kafka-setup-avn
description: > Use when this capability is needed. End-to-end workflow for creating an Apache Kafka service o…
category: 通用
source: tomevault-io/skills-registry
---
# aiven-kafka-setup-avn
## 什么时候使用
- 把通用方向的常用动作沉淀成 Agent 可调用的技能 适合处理通用任务拆解、检查、交付和复盘,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查、可继续迭代的步骤;通常不需要额外…
- 面向通用任务拆解、检查和交付,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Step 1: Prerequisites / 1.1 Verify avn CLI login / 1.2 Required tools」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令、读取环境变量;主要在本地完成;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "aiven-kafka-setup-avn" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Step 1: Prerequisites / 1.1 Verify avn CLI login / 1.2 Required tools
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> Python | 读取文件、写入/修改文件、执行终端命令、读取环境变量 | 主要在本地完成
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} Aiven Kafka Setup (avn CLI)
End-to-end workflow for creating an Apache Kafka service on Aiven using the avn CLI,
with SASL_SSL authentication, Avro Schema Registry, and a working Java or Python
producer/consumer example that reads from CSV and writes to Kafka.
IMPORTANT: This skill ALWAYS creates a fully working example (Java by default). Steps 1–3 are all mandatory. Never stop after creating the service — you MUST also build the example project, generate test data, and run the producer + consumer end-to-end.
Step 1: Prerequisites
1.1 Verify avn CLI login
Run the following to check if the user is logged in:
avn user info
If the command fails, inspect the error and guide the user accordingly:
If the error contains "Expired db token":
Your Aiven login token expired. Please run:
avn user login <your-email>
If the error contains "ERROR: Not logged in" or "UserError: not authenticated":
You are not logged in to the Aiven CLI. Please run:
avn user login <your-email>
If you are a new user, create an account via:
https://console.aiven.io/login
Then confirm when you are logged in.
STOP and wait for the user to confirm login before proceeding.
1.2 Required tools
Verify the following are installed:
avn(Aiven CLI) - At least version 4.7.0 or later is required.jq(JSON processing)- For Java:
java(17+),mvn - For Python:
python3(3.9+),pip
Before creating a service, ask the customer to confirm they have enough credits (they can check with):
avn project details --json
Use the AskQuestion tool to collect this confirmation without interrupting the flow.
AI Agent MUST NOT check credits itself. Only the customer should run the credit-check command and confirm.
Missing Requirements Policy:
- If a library or CLI tool (like
avn) is missing, advise the user on how to install it (e.g.,python3 -m pip install aiven-clientforavn). However, check first ifpython3is available before suggesting apipcommand. - If a core language runtime (
python3orjava) is requested but missing, interrupt the flow immediately. Do NOT advise the user on how to install programming languages.
Step 2: Create the Kafka Service and Export Environment Variables
Follow SERVICE_CREATION_AVN.md sections 1–4 in order:
- Choose a service name (if missing) — if the customer did not provide a service name, use AskQuestion with:
aiven-kafka-service-testOther(if selected, ask the customer to provide their custom service name)
- Choose a region — ask the user with AskQuestion, mapping their choice to the EXACT
CLOUD_NAMEfrom the table in SERVICE_CREATION_AVN.md. - Choose a plan — default
developer-2-1d; never usefree-0orstartup-2. - Run the setup script — a single command creates the service, tags it with
AI-skill-generated=true, creates users and ACLs, registers the schema, extracts all connection details, and writes them toenv.sh.- If service creation returns
Payment method is not set and there is not enough credits for the service, the script fails fast and the flow must stop immediately.
- If service creation returns
- Source
env.sh— loadsKAFKA_HOST,KAFKA_PORT,SCHEMA_REGISTRY_URL,AVNADMIN_PASS,PRODUCER_PASSWORD,CONSUMER_PASSWORDinto the shell.
bash scripts/setup_aiven_kafka.sh <name> <CLOUD_NAME> <plan> 4.1
source env.sh
CRITICAL: Do NOT read or cat
env.shin the agent context — it contains passwords. Onlysourceit and verify passwords by${#VAR}(length).
Step 3: Create and Run the Working Example
MANDATORY: This step is NOT optional. After the Kafka service is running and environment variables are exported, you MUST create a working producer/consumer example, compile/install it, generate test data, and run it end-to-end. Default language is Java unless the user explicitly requests Python.
3.1 Ask the user which language to use
Use the AskQuestion tool:
Prompt: "Which language for the producer/consumer example?"
Options:
- Java (default, recommended)
- Python
If the user requests a language other than Java or Python, warn them:
"Results with languages other than Java or Python are unpredictable. It is recommended to use Java or Python for reliable results."
If the user does not answer or skips, default to Java.
3.2 Copy templates into the workspace
The templates live under this skill's templates/ directory. They MUST be copied to
the workspace root so the run scripts can find them at the expected relative paths.
# Copy from the skill directory into the workspace root
cp -r <SKILL_DIR>/templates/ <WORKSPACE_ROOT>/templates/
cp -r <SKILL_DIR>/scripts/ <WORKSPACE_ROOT>/scripts/
After copying, verify the files exist:
ls templates/order.avsc
ls templates/producer_consumer_java/Producer.java # if Java
ls templates/producer_consumer_python/producer.py # if Python
ls scripts/run_producer.sh scripts/run_consumer.sh
3.3 Generate test data
Run the data generator (no external dependencies):
python3 scripts/generate_orders.py
This creates orders.csv with 20 rows in the format id,user_id,product,price.
Verify it was created:
wc -l orders.csv # should show 21 (1 header + 20 data rows)
3.4 Build the project
Java (default)
Set up the Maven source tree and compile:
JAVA_DIR="templates/producer_consumer_java"
mkdir -p "$JAVA_DIR/src/main/java/com/aiven/demo"
cp "$JAVA_DIR/Producer.java" "$JAVA_DIR/src/main/java/com/aiven/demo/"
cp "$JAVA_DIR/Consumer.java" "$JAVA_DIR/src/main/java/com/aiven/demo/"
cp "$JAVA_DIR/Order.java" "$JAVA_DIR/src/main/java/com/aiven/demo/"
mvn -f "$JAVA_DIR/pom.xml" package -DskipTests
Verify the JAR was created:
ls "$JAVA_DIR/target/kafka-orders-demo-1.0-SNAPSHOT.jar"
If compilation fails, check that java (17+) and mvn are installed.
Python (if selected)
Install dependencies:
python3 -m pip install -r templates/producer_consumer_python/requirements.txt
Verify the install succeeded:
python3 -c "import confluent_kafka; print(confluent_kafka.version())"
3.5 Run the producer (start FIRST)
The producer MUST run first to publish messages into Kafka. The consumer reads
them afterwards (the consumer uses auto.offset.reset=earliest, so it will pick up
all messages from the beginning of the topic regardless of when it starts).
bash scripts/run_producer.sh <java|python>
Wait for the producer to finish (it will print "Done. Produced 20 messages.").
3.6 Run the consumer
After the producer has finished, start the consumer to read and process the messages:
bash scripts/run_consumer.sh <java|python>
The consumer will read all 20 messages (starting from the earliest offset), write
them to orders_completed.csv, and then exit (both Java and Python exit
automatically after consuming the expected 20 records).
3.7 Verify output
python3 scripts/verify_output.py
This checks that orders_completed.csv has 20 rows with correct columns and all
completed_at timestamps populated.
If verification fails, check:
- The producer finished successfully before the consumer was started
- Environment variables (
KAFKA_HOST,KAFKA_PORT, etc.) are all set - The
cert/ca.pemfile exists - For Java: the JAR exists in
templates/producer_consumer_java/target/ - For Python:
confluent_kafkais installed
Step 4: Teardown Information
DO NOT run teardown automatically. Instead, inform the user how to clean up when they are ready:
When you're done with the demo, you can tear down the service by running:
bash scripts/teardown.sh "$KAFKA_SERVICE"This will delete the Aiven Kafka service, remove the local
cert/directory, and clean up generated CSV files.
For detailed avn CLI command reference and troubleshooting, see reference.md.
File Reference
| File | Purpose |
|---|---|
| SERVICE_CREATION_AVN.md | Region/plan selection (interactive), then delegates to setup script |
| reference.md | avn CLI cheat sheet, region map, troubleshooting |
| templates/order.avsc | Avro schema for orders topic |
| templates/producer_consumer_java/ | Java Producer + Consumer + pom.xml |
| templates/producer_consumer_python/ | Python producer + consumer + requirements.txt |
| scripts/generate_orders.py | Generate orders.csv (20 rows) |
| scripts/setup_aiven_kafka.sh | Full setup: service, users, ACLs, schema, env.sh |
| scripts/run_producer.sh | Run producer (Java or Python) |
| scripts/run_consumer.sh | Run consumer (Java or Python) |
| scripts/verify_output.py | Validate orders_completed.csv |
| scripts/teardown.sh | Delete service and clean up |
Source: Aiven-Open/aiven-skills-bundle — distributed by TomeVault.
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核