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AI-powered DP Data Processing Pipeline Designer

作者 Hxp365 · GitHub ↗ · v2.0.1 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install dp-pipeline-designer
功能描述
DP 数据处理平台流水线设计师。当用户提到创建管道、数据流、Flink作业、Kafka读取、写到数据库/MongoDB、数据处理管道等需求时激活。
使用说明 (SKILL.md)

dp-pipeline-designer

Purpose

Design, generate, submit, and monitor DP Data Processing Platform pipelines from natural language descriptions. This skill acts as an AI front-end to the DP platform's REST API, translating user requirements into runnable Apache Flink data pipelines.

The DP platform runs at ${DP_SERVER_URL} by default.

Environment Configuration

The DP platform runs at ${DP_SERVER_URL}.

Required environment variables:

DP_SERVER_URL=${DP_SERVER_URL}   # REQUIRED — DP platform base URL
DP_API_KEY=${DP_API_KEY}         # REQUIRED — obtain from platform「API Key 管理」page

ALL curl commands MUST use -H 'X-DP-API-Key: ${DP_API_KEY}'. No other authentication method is supported.

首次使用引导

# 校验 DP_API_KEY — 未配置则终止
if [ -z "${DP_API_KEY}" ]; then
  echo "======================================"
  echo "  DP Platform — API Key 必填"
  echo "======================================"
  echo "错误:未检测到 DP_API_KEY,无法继续。"
  echo ""
  echo "请按以下步骤配置:"
  echo "1. 访问 DP 平台控制台:${DP_SERVER_URL}"
  echo "2. 注册账号(如需邀请码请联系管理员)"
  echo "3. 进入「API Key 管理」→「申请新 Key」"
  echo "4. 将生成的 Key 配置到 DP_API_KEY 环境变量"
  echo ""
  echo "免费版:100次/月。超额后需升级订阅套餐。"
  echo "======================================"
  exit 1
fi
echo "API Key 已验证:${DP_API_KEY:0:8}****"

配额说明

  • 免费版:100 次/月 API 调用额度
  • 超额时响应中会包含 quota_exceeded: true 字段
  • 响应中的 upgrade_url 字段指向订阅升级页面
  • 升级套餐可获得更多额度:BASIC(1000次)、PRO(10000次)、ENTERPRISE(不限)

Capabilities

  • Ask clarifying questions to understand data source, transformation logic, and output target
  • Generate a complete StreamJob XML configuration
  • Submit the job via REST API and start execution
  • Poll job status and report progress per operator
  • Retrieve error logs and suggest root-cause fixes
  • Support 4 built-in industry scenario templates

Context Files

The following files provide the knowledge base for this skill:

File Purpose
dp-operator-catalog.json Complete list of 60+ operators with params and pipeline templates
dp-api-reference.md REST API endpoints, parameters, and curl examples
dp-job-schema.md StreamJob XML format, examples, and encoding rules

Workflow

Phase 1: Requirements Gathering

When the user describes a pipeline need, ask ALL of the following if not already specified:

  1. Data Source: Where does data come from?
  2. Transformations: What should happen to the data?
  3. Output Target: Where should results go?
  4. Schedule: How should the job run?
  5. Resources: What connections are already configured?

Phase 2-5: Pipeline Design, XML Generation, Job Submission, Status Monitoring

See full SKILL.md for complete implementation details.

Limitations & Guardrails

  1. Only use operators listed in dp-operator-catalog.json
  2. Always show the design to the user for confirmation before generating XML
  3. Do not store passwords in XML files — use resourceId references
  4. If DP Server is unreachable, guide user to start services
  5. Parallelism default is 1 for new jobs

License

MIT-0: Free to use, modify, and redistribute. No attribution required.

安全使用建议
This skill largely matches its stated function (it will call your DP platform API using DP_SERVER_URL and DP_API_KEY), but it references supporting files (dp-operator-catalog.json, dp-api-reference.md, dp-job-schema.md) that are not included—ask the publisher where those files come from. Before installing: 1) Confirm the DP_SERVER_URL is the legitimate platform you expect (the skill metadata even shows an example IP you should verify). 2) Only provide a least-privilege API key for testing (not a full-admin key) and test in a non-production environment. 3) Request the missing context files or documentation to understand what operators/templates the skill will use. 4) If you cannot verify the source of the context files or the publisher, avoid supplying secrets to this skill.
功能分析
Type: OpenClaw Skill Name: dp-pipeline-designer Version: 2.0.1 The skill is a legitimate-appearing tool designed to interface with a 'DP Data Processing Platform' for managing Flink-based data pipelines. It uses standard REST API interactions (via curl) and requires user-provided environment variables (DP_SERVER_URL and DP_API_KEY). The instructions in SKILL.md and the configuration in skill.json are consistent with the stated purpose of pipeline design and monitoring, and the included bash script is a simple validation check for required credentials with no evidence of malicious intent or data exfiltration.
能力评估
Purpose & Capability
The skill claims to design, generate, submit, and monitor DP platform Flink jobs and therefore legitimately needs DP_SERVER_URL and DP_API_KEY. However, the SKILL.md references three context files (dp-operator-catalog.json, dp-api-reference.md, dp-job-schema.md) that are not included in the package, which is an inconsistency: either the skill will be non-functional or expects external files not disclosed.
Instruction Scope
Instructions are focused on talking to the DP REST API (submit jobs, poll status, retrieve logs) and only reference the declared DP env vars. They do not instruct the agent to read unrelated system files or exfiltrate data. The initial-shell snippet will abort if DP_API_KEY is not set and prints a masked API key prefix; this is benign but reveals part of the key locally. Overall scope is appropriate but depends on missing context files.
Install Mechanism
Instruction-only skill with no install spec and no code files, so nothing is written to disk by an installer. This is the lowest-risk install model.
Credentials
Only DP_SERVER_URL and DP_API_KEY are required, which is proportionate for a REST-API integrator. Minor concern: skill.json includes an explicit example IP (http://8.130.64.180) in the env var description — presence of a hard-coded example IP in metadata is unexpected and should be validated.
Persistence & Privilege
The skill does not request always:true and is user-invocable; it does not request elevated or persistent platform privileges. Autonomous invocation is allowed (platform default) but not combined with other red flags.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install dp-pipeline-designer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /dp-pipeline-designer 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v2.0.1
**Summary:** Documentation streamlined and environment configuration simplified for ease of use. - Removed guidance for session-based authentication; API Key authentication is now mandatory and simplified. - Clarified required environment variables and setup steps. - Dropped references to file-based secrets and install scripts — now relies only on environment variables. - Added a summary of skill knowledge base/context files. - Expanded section on limitations and usage guardrails. - General editing for clarity and brevity throughout the documentation.
v2.0.0
dp-pipeline-designer 2.0.0 - Added initial SKILL.md documentation with test content.
元数据
Slug dp-pipeline-designer
版本 2.0.1
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 2
常见问题

AI-powered DP Data Processing Pipeline Designer 是什么?

DP 数据处理平台流水线设计师。当用户提到创建管道、数据流、Flink作业、Kafka读取、写到数据库/MongoDB、数据处理管道等需求时激活。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 121 次。

如何安装 AI-powered DP Data Processing Pipeline Designer?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install dp-pipeline-designer」即可一键安装,无需额外配置。

AI-powered DP Data Processing Pipeline Designer 是免费的吗?

是的,AI-powered DP Data Processing Pipeline Designer 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

AI-powered DP Data Processing Pipeline Designer 支持哪些平台?

AI-powered DP Data Processing Pipeline Designer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 AI-powered DP Data Processing Pipeline Designer?

由 Hxp365(@hxp365)开发并维护,当前版本 v2.0.1。

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