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Agent Skill · 待分类

sap-datasphere(SAP 数据圈)

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

sap-datasphere 是待分类类 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;许可证为 MIT,第三方扫描已通过,按安装量在待分类类的 11,209 个 Skill 里排第 1,979。

总安装 2,007周安装 82GitHub Stars 239下载 643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
MIT

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:sap-datasphere(SAP 数据圈)
来源仓库:https://github.com/secondsky/sap-skills
仓库路径:skills/sap-datasphere
安装命令:
npx skills add https://github.com/secondsky/sap-skills --skill sap-datasphere
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/secondsky/sap-skills --skill sap-datasphere

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

用于辅助数据整理、表格处理和指标计算。sap-datasphere 属于待分类类 Skill,可作为该场景下的辅助能力补充。适合清洗字段、汇总数据、发现异常并生成统计口径。使用时需确认数据来源、字段含义和时间范围。涉及敏感数据导出时应先确认权限和脱敏边界。

通过 npx skills add 命令从 GitHub 仓库安装使用。

来源仓库内路径:skills/sap-datasphere

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/secondsky/sap-skills --skill sap-datasphere;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

sap-datasphere 怎么安装?

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

sap-datasphere 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。

sap-datasphere 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/secondsky/sap-skills --skill sap-datasphere;npx skills add secondsky/sap-skills --skill "sap-datasphere" 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。

sap-datasphere 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

sap-datasphere 用的人多吗?

公开数据是累计安装 2,007 次,近一周安装 82 次,下载 643 次,GitHub 239 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。

sap-datasphere 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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。
  • 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。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
sap-datasphere

SAP 数据圈 · 本页

2,007239执行命令MIT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

SAP Datasphere Skill

Table of Contents

- Core Components - Object Types

- Graphical Views - SQL Views - Tables - Flows - Task Chains

Overview

SAP Datasphere is SAP's cloud-native data warehouse solution on SAP Business Technology Platform (BTP). This skill provides comprehensive guidance for data acquisition, preparation, modeling, administration, and integration.

Use this skill when:

  • Creating data warehouses on SAP BTP
  • Building analytic models for SAP Analytics Cloud
  • Setting up data flows, replication flows, or transformation flows
  • Configuring connections to SAP or third-party systems
  • Managing spaces, users, and access controls
  • Implementing real-time data replication
  • Monitoring data integration tasks

Quick Reference

Core Components

ComponentPurposeKey Objects
Data BuilderData acquisition & preparationViews, Tables, Flows, Task Chains
Business BuilderSemantic layer modelingBusiness Entities, Fact Models, Consumption Models
Analytic ModelAnalytics-ready structuresDimensions, Facts, Measures, Hierarchies
ConnectionsExternal data sources40+ connection types
SpacesLogical data containersStorage, Users, Objects

Object Types

Views:

  • Graphical View: Visual data modeling with drag-and-drop
  • SQL View: SQL-based view definitions
  • Analytic Model: Analytics-optimized semantic layer

Tables:

  • Local Table: Data stored in Datasphere
  • Remote Table: Virtual access to external data
  • Local Table (File): Object store-based storage

Flows:

  • Data Flow: ETL transformations
  • Replication Flow: Data replication from sources
  • Transformation Flow: Delta-aware transformations

Data Builder

Graphical Views

Create views visually by dragging sources and adding transformations.

Supported Operations:

  • Join: Inner, Left Outer, Right Outer, Full Outer, Cross
  • Union: Combine multiple sources
  • Projection: Select/rename columns
  • Filter: Row-level filtering
  • Aggregation: Group by with aggregates
  • Calculated Columns: Derived values

Best Practices:

  • Use input parameters for dynamic filtering
  • Apply data access controls for row-level security
  • Enable persistence for frequently accessed views
  • Use lineage analysis to understand dependencies

For detailed graphical view operations, see references/graphical-sql-views.md.

SQL Views

Create views using SQL or SQLScript.

-- Basic SQL View
SELECT
    customer_id,
    customer_name,
    SUM(order_amount) AS total_orders
FROM orders
GROUP BY customer_id, customer_name

SQLScript Support:

  • Table variables
  • Scalar variables
  • Control flow (IF, WHILE, FOR)
  • Exception handling

For SQL/SQLScript reference, see references/graphical-sql-views.md.

Data Flows

ETL pipelines for data transformation and loading.

Operators:

  • Source: Remote/local tables, views
  • Target: Local tables
  • Join, Union, Projection, Filter, Aggregation
  • Script: Python custom logic
  • Calculated Columns

Execution:

  • Manual run or scheduled via task chains
  • Delta capture for incremental loads
  • Input parameters for runtime configuration

For data flow details, see references/data-acquisition-preparation.md.

Replication Flows

Replicate data from source systems to Datasphere or external targets.

Supported Sources:

  • SAP S/4HANA (Cloud/On-Premise)
  • SAP BW/4HANA
  • SAP ECC
  • ABAP-based systems
  • Cloud storage (S3, Azure Blob, GCS)
  • Kafka/Confluent
  • SFTP

Supported Targets:

  • SAP Datasphere (local tables)
  • Apache Kafka
  • Google BigQuery
  • Cloud storage providers
  • SAP Signavio

Load Types:

  • Initial Load: Full data extraction
  • Delta Load: Changed data only
  • Real-Time: Continuous replication

For replication flow configuration, see references/data-acquisition-preparation.md.

Transformation Flows

Delta-aware transformations with automatic change propagation.

Key Features:

  • Automatic delta detection
  • Target table management
  • Graphical or SQL view as source
  • Run modes: Start, Delete, Truncate

For transformation flow details, see references/data-acquisition-preparation.md.

Task Chains

Orchestrate multiple tasks in sequence or parallel.

Supported Tasks:

  • Data flows
  • Replication flows
  • Transformation flows
  • Remote table replication
  • View persistence
  • Open SQL procedures
  • API tasks
  • BW Bridge process chains

Features:

  • Parallel execution branches
  • Input parameters
  • Email notifications
  • Nested task chains
  • Scheduling (simple or cron)

Data Modeling

Analytic Models

Create analytics-ready semantic models for SAP Analytics Cloud.

Components:

  • Fact: Contains measures (quantitative data)
  • Dimension: Categorizes data (master data)
  • Measure: Quantifiable metrics
  • Hierarchy: Navigation structures
  • Variable: Runtime parameters

Creating an Analytic Model:

  1. Add a fact source (view or table)
  2. Add dimension associations
  3. Define measures with aggregation
  4. Configure variables for filtering
  5. Set data access controls

For detailed modeling guidance, see references/data-modeling.md.

Dimensions

Categorize and filter analytical data.

Types:

  • Standard: Basic categorical data
  • Time: Calendar-based filtering
  • Fiscal Time: Custom fiscal calendars
  • Text Entity: Multilingual labels

Features:

  • Hierarchies (level-based, parent-child)
  • Time dependency (SCD Type 2)
  • Compound keys
  • Associated text entities

Measures

Quantifiable values for analysis.

Types:

  • Simple: Direct aggregation
  • Calculated: Derived from other measures
  • Restricted: Filtered aggregation
  • Currency Conversion: Dynamic conversion
  • Unit Conversion: Dynamic conversion
  • Count Distinct: Unique value count
  • Non-Cumulative: Point-in-time values

Aggregation Types:

  • SUM, MIN, MAX, COUNT, AVG
  • Exception aggregation for non-additive scenarios

For measure configuration, see references/data-modeling.md.

Business Builder

Create business-oriented semantic models.

Objects:

  • Business Entity: Reusable dimension/fact definitions
  • Fact Model: Combines business entities
  • Consumption Model: Analytics-ready model
  • Authorization Scenario: Row-level security

For Business Builder details, see references/data-modeling.md.


Connectivity

Connection Types

SAP Datasphere supports 40+ connection types.

SAP Systems:

  • SAP S/4HANA Cloud/On-Premise
  • SAP BW/4HANA (Model Transfer)
  • SAP BW Bridge
  • SAP ECC
  • SAP HANA (Cloud/On-Premise)
  • SAP SuccessFactors
  • SAP Fieldglass
  • SAP Marketing Cloud
  • SAP Signavio

Cloud Platforms:

  • Amazon S3, Athena, Redshift
  • Google Cloud Storage, BigQuery
  • Microsoft Azure Blob, Data Lake, SQL Database
  • Microsoft OneLake

Databases:

  • Oracle
  • Microsoft SQL Server
  • Generic JDBC

Streaming:

  • Apache Kafka
  • Confluent

Other:

  • Generic OData, HTTP, SFTP
  • Adverity, Precog
  • SAP Open Connectors

For connection configuration, see references/connectivity.md.

Connection Features

FeatureDescription
Remote TablesVirtual data access
Data FlowsETL transformation
Replication FlowsData replication
Model ImportBW/4HANA model transfer

Administration

Spaces

Logical containers for data and objects.

Configuration:

  • Storage allocation (disk + in-memory)
  • User access and roles
  • Priority and statement limits
  • Workload management

Operations:

  • Create, copy, delete spaces
  • Export/import space data
  • Command-line management (datasphere CLI)

For space management, see references/administration.md.

Users and Roles

Standard Roles:

  • DW Administrator
  • DW Space Administrator
  • DW Integrator
  • DW Modeler
  • DW Viewer

Scoped Roles:

  • Space-specific permissions
  • Custom privilege combinations

Authentication:

  • SAP Cloud Identity Services
  • Custom SAML IdP
  • OAuth 2.0 clients

For user management, see references/administration.md.

Monitoring

Capabilities:

  • Capacity monitoring (storage, memory, compute)
  • Audit logs (database operations)
  • Activity logs (object changes)
  • Task logs (flow executions)

Database Analysis:

  • Create analysis users for debugging
  • Monitor HANA views
  • Stop running statements

For monitoring details, see references/administration.md.


Data Integration Monitor

Remote Tables

Operations:

  • Replicate data (full/delta/real-time)
  • Partition data loads
  • Create statistics
  • Monitor queries

Real-Time Replication

Features:

  • Continuous change capture
  • Pause/resume capability
  • Automatic recovery
  • Watermark tracking

View Persistence

Options:

  • Scheduled refresh
  • On-demand refresh
  • Partition management
  • Memory optimization

For monitoring details, see references/data-integration-monitor.md.


CLI Reference

Datasphere CLI Overview

The datasphere CLI enables command-line administration and automation.

Installation:

npm install -g @sap/datasphere-cli

Authentication:

# Interactive login
datasphere config auth login

# Service key (CI/CD)
datasphere config auth login --service-key-path ./key.json

Core Commands:

CommandPurpose
datasphere spaces listList all spaces
datasphere spaces createCreate a space
datasphere objects exportExport objects
datasphere objects importImport objects
datasphere tasks runExecute task chains
datasphere marketplace listList marketplace products

CI/CD Integration:

# Export and import workflow
datasphere objects export --space DEV --output-file package.zip
datasphere objects import --space PROD --input-file package.zip --overwrite

For complete CLI reference, see references/cli-commands.md.


Data Products & Marketplace

Creating Data Products

Package curated data for internal or external consumption:

  1. Plan: Define purpose, target consumers, contents
  2. Prepare: Create views/models, set semantic usage, document
  3. Configure: Set visibility, access controls, terms
  4. Publish: Make available in marketplace

Product Components:

  • Core assets (views, models, entities)
  • Documentation and sample queries
  • Governance metadata (owner, quality score, SLA)

Data Marketplace

Discover and consume published data products:

  • Search: Find by category, provider, quality
  • Request Access: Submit justification, await approval
  • Consume: Use in views or SAC stories

For complete marketplace guidance, see references/data-products-marketplace.md.


Catalog & Governance

Data Catalog Features

Centralized discovery and governance:

  • Asset Discovery: Search all data objects with metadata
  • Glossary: Standardized business term definitions
  • Data Quality: Automated quality rules and scoring
  • Lineage: Trace data from source to consumption
  • Classification: Sensitivity levels and compliance tags

Governance Workflow

Create Object → Add Metadata → Link Terms → Quality Check → Approve → Publish

Roles:

  • Data Owner: Business accountability
  • Data Steward: Quality and metadata management
  • Data Custodian: Technical implementation

For detailed governance guidance, see references/catalog-governance.md.


Data Access Controls

Implement row-level security.

Types:

  • Single Values: Simple value matching
  • Operator and Values: Complex conditions
  • Hierarchy: Node-based filtering
  • Hierarchy with Directory: Hierarchical permissions

Application:

  • Apply to views or analytic models
  • Based on user attributes
  • Import from SAP BW Analysis Authorizations

For security configuration, see references/data-access-security.md.


Content Transport

Move content between tenants.

Methods:

  • Export/Import packages
  • SAP Cloud Transport Management
  • CSN/JSON file export

Package Contents:

  • Views, tables, flows
  • Connections (metadata only)
  • Spaces configuration

For transport procedures, see references/content-transport.md.



Common Errors and Solutions

ErrorCauseSolution
Deployment failedCircular dependencyCheck object dependencies
Connection timeoutNetwork/firewallVerify Cloud Connector/IP allowlist
Replication stuckSource lockCheck source system status
Out of memoryLarge viewEnable persistence or partitioning
Permission deniedMissing roleVerify space membership and privileges

Bundled Resources

Reference Documentation

Core Data Builder:

  1. references/data-acquisition-preparation.md - Data flows, replication flows, transformation flows, and table management
  2. references/graphical-sql-views.md - Graphical views, SQL views, E-R models, and intelligent lookups
  3. references/data-modeling.md - Business Builder entities, analytic models, dimensions, measures, and hierarchies

Connectivity & Integration: 4. references/connectivity.md - All 40+ connection types including SAP systems, cloud providers, and streaming platforms 5. references/data-integration-monitor.md - Task scheduling, monitoring, real-time replication, and delta mechanisms

Administration & Security: 6. references/administration.md - Tenant management, space configuration, user roles, and elastic compute nodes 7. references/data-access-security.md - Row-level security, DAC configurations, and authorization scenarios 8. references/content-transport.md - Package export/import, transport management, and tenant migration

CLI & Automation: 9. references/cli-commands.md - Complete CLI reference, authentication, CI/CD integration patterns

Marketplace & Governance: 10. references/data-products-marketplace.md - Creating and consuming data products, provider workflows, pricing 11. references/catalog-governance.md - Data catalog, glossary, quality rules, lineage, classification

Best Practices & Updates: 12. references/best-practices-patterns.md - Architecture patterns, naming conventions, performance optimization, checklists 13. references/whats-new-2025.md - Q1-Q4 2025 features, Generic HTTP, REST API tasks, deprecations

MCP Integration: 14. references/mcp-tools-reference.md - Complete MCP tool reference, 45 tools across 8 categories, API documentation, authentication patterns 15. references/mcp-use-cases.md - 8 real-world use cases with personas, time savings, and ROI analysis ($159K+/year savings)

Plugin Components

This plugin includes 3 specialized agents, 5 slash commands, and validation hooks:

Agents (in agents/):

  • datasphere-modeler - Data Builder tasks, views, flows, analytic models
  • datasphere-integration-advisor - Connectivity, replication, data integration
  • datasphere-admin-helper - Space management, security, monitoring

Commands (in commands/):

  • /datasphere-space-template - Generate space configurations
  • /datasphere-view-template - Generate view templates (graphical/SQL)
  • /datasphere-connection-guide - Step-by-step connection setup
  • /datasphere-cli - CLI command reference and examples

Hooks (in hooks/):

  • PreToolUse validation for SQL/SQLScript code quality
  • PostToolUse suggestions for persistence and optimization

MCP Integration

This skill integrates with the SAP Datasphere MCP Server (@mariodefe/sap-datasphere-mcp) providing 45 tools for live tenant interaction.

MCP Tools

The MCP server enables:

  • Direct Queries: Execute SQL and smart queries on live data
  • Metadata Access: Inspect tables, views, and analytic models
  • User Management: Create, update, delete database users
  • Catalog Search: Find assets by name or column
  • Connection Testing: Verify connectivity and tenant info
  • Data Profiling: Analyze column distributions

See /datasphere-mcp-tools command for complete tool list.

Authentication

OAuth 2.0 Client Credentials with automatic token refresh.

Required environment variables:

  • DATASPHERE_BASE_URL
  • DATASPHERE_CLIENT_ID
  • DATASPHERE_CLIENT_SECRET
  • DATASPHERE_TOKEN_URL

Performance

  • Sub-100ms metadata queries (cached)
  • 100-500ms catalog operations
  • 500-2,000ms OData queries
  • Batch processing up to 50,000 records

File Structure

plugins/sap-datasphere/
├── .claude-plugin/
│   └── plugin.json
├── .mcp.json                         # MCP server configuration
├── agents/
│   ├── datasphere-modeler.md
│   ├── datasphere-integration-advisor.md
│   └── datasphere-admin-helper.md
├── commands/
│   ├── datasphere-space-template.md
│   ├── datasphere-view-template.md
│   ├── datasphere-connection-guide.md
│   ├── datasphere-cli.md
│   └── datasphere-mcp-tools.md       # MCP tools reference
├── hooks/
│   └── hooks.json
└── skills/
    └── sap-datasphere/
        ├── .claude-plugin/
        │   └── plugin.json
        ├── SKILL.md
        ├── README.md
        └── references/
            ├── data-acquisition-preparation.md
            ├── data-modeling.md
            ├── graphical-sql-views.md
            ├── connectivity.md
            ├── administration.md
            ├── data-integration-monitor.md
            ├── data-access-security.md
            ├── content-transport.md
            ├── cli-commands.md
            ├── data-products-marketplace.md
            ├── catalog-governance.md
            ├── best-practices-patterns.md
            ├── whats-new-2025.md
            └── mcp-tools-reference.md    # MCP technical reference

Documentation Links


Version: 2.1.0 | Last Verified: 2025-12-28

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执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/secondsky/sap-skills --skill sap-datasphere;npx skills add secondsky/sap-skills --skill "sap-datasphere" 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。

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