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sap-sac-planning 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

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请帮我安装这个 Agent Skill:sap-sac-planning(SAP sac 规划)
来源仓库:https://github.com/secondsky/sap-skills
仓库路径:skills/sap-sac-planning
安装命令:
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简介

用于处理 GitHub 仓库、Issue 和 Pull Request 协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕代码变更进行整理。
  • 通过 npx skills add 命令从 GitHub 仓库安装使用。
  • 建议确认权限范围和维护状态,避免触发联网或文件读写操作。
  • 可结合原始 README 进一步核验具体用法和功能边界。

SKILL.md

SAP Analytics Cloud Planning Skill

Comprehensive skill for building enterprise planning applications with SAP Analytics Cloud.


Reference Add-Ons (2025.25)

  • Execution guides: references/data-actions.md, references/multi-actions.md, references/allocations.md, references/scheduling-calendar.md, references/data-locking.md
  • Modeling & governance: references/modeling-basics.md, references/version-management.md, references/version-edit-modes.md, references/version-publishing-notes.md
  • Calculations & intelligence: references/advanced-formulas.md, references/predictive-conversion.md, references/ai-planning-analytics.md, references/api-snippets.md
  • Workflow aids: references/input-tasks.md, references/job-monitoring.md
  • New in 2025: references/seamless-planning-datasphere.md, references/bpc-live-connection.md, references/value-driver-trees.md, references/data-action-tracing.md
  • Ready-to-use templates: templates/data-action-checklist.md, templates/multi-action-checklist.md, templates/parameter-table.md

Use these to keep instructions concise in this file while deep-dives remain one click away.


Table of Contents

When to Use This Skill

Use this skill when working on tasks involving:

Planning Application Development:

  • Creating planning-enabled stories with data entry
  • Building analytics designer applications for planning
  • Implementing input forms and planning tables
  • Configuring planning models with Version and Date dimensions
  • Setting up data sources for planning scenarios

Data Actions & Multi Actions:

  • Creating data actions for copy, allocation, and calculations
  • Building multi actions to orchestrate planning operations
  • Configuring parameters (member, number, string, datetime types)
  • Implementing embedded data actions
  • Setting up API steps for external integrations

Version Management:

  • Managing public and private versions
  • Publishing workflows (Publish As, Publish Private Data)
  • Sharing private versions with collaborators
  • Version creation and deletion via API

Planning Workflows:

  • Setting up calendar-based planning processes
  • Creating general tasks, review tasks, and composite tasks
  • Implementing multi-level approval workflows
  • Configuring data locking tasks
  • Managing task dependencies

JavaScript Planning APIs:

  • Using getPlanning() API for data entry
  • Working with PlanningModel API for master data
  • Implementing DataSource API for filtering and querying
  • Writing scripts for planning automation
  • Handling version management via API

Data Entry & Allocation:

  • Implementing spreading (to child members)
  • Configuring distribution (between siblings)
  • Setting up rule-based allocations
  • Copy/paste operations in planning tables
  • Using advanced formulas for calculations

Data Locking:

  • Configuring data locking on models
  • Setting up lock states (locked, restricted, open)
  • Creating data locking tasks in calendar
  • Implementing event-based data locking
  • Integrating data locking in multi actions

Seamless Planning with Datasphere (2025):

  • Planning models with Datasphere storage
  • Cross-model planning with unified data
  • Direct persistence to Datasphere
  • Enterprise data governance for planning

BPC Live Connection:

  • Planning with BPC Embedded on S/4HANA
  • Running BPC planning sequences from SAC
  • Master data planning via BPC
  • Live data connection configuration

Value Driver Trees:

  • Building business value chain visualizations
  • What-if analysis and scenario simulation
  • Driver-based planning
  • Interactive planning dashboards

Data Action Debugging:

  • Tracing data action execution
  • Adding tracepoints for debugging
  • Analyzing intermediate results
  • Troubleshooting allocation issues

Quick Start

Creating a Planning-Enabled Story

  1. Create Planning Model with required dimensions:

- Version dimension (required) - Date dimension (required) - Account dimension (recommended) - Other business dimensions

  1. Add Table Widget to story and link to planning model
  2. Enable Planning on the table:

- Select table → Planning panel → Enable Planning - Configure version selection (public or private)

  1. Configure Data Entry:

- Set editable measures/accounts - Configure spreading behavior - Set up validation rules

Creating an Analytics Designer Planning Application

  1. Create Analytic Application (not Optimized Story)
  2. Add Planning Model as data source
  3. Add Table Widget and enable planning
  4. Write Scripts for:

- Version selection - Data submission - Custom validation - Workflow triggers


Core Concepts

Model Types

Planning Model:

  • Supports data write-back
  • Requires Version and Date dimensions
  • Enables spreading, distribution, allocation
  • Supports data locking
  • Used for budgeting, forecasting, planning

Analytic Model:

  • Read-only (no write-back)
  • No required dimensions
  • Better performance for reporting
  • Use when planning not needed

Version Management

Public Versions:

  • Visible to all users with access
  • Shared across the organization
  • Require publish to update

Private Versions:

  • Visible only to creator (unless shared)
  • Used for simulation and what-if analysis
  • Can be published to public or new version

Edit Mode:

  • Temporary private copy when editing public version
  • Changes visible only to editor until published
  • Automatic validation on publish

Reference: See references/version-management.md for detailed workflows.

Planning API Overview

getPlanning() API - Table planning operations:

// Check if planning is enabled
var isEnabled = Table_1.getPlanning().isEnabled();

// Get public versions
var publicVersions = Table_1.getPlanning().getPublicVersions();

// Get private version
var privateVersion = Table_1.getPlanning().getPrivateVersion();

// Set user input (data entry)
Table_1.getPlanning().setUserInput(selection, value);

// Submit data changes
Table_1.getPlanning().submitData();

PlanningModel API - Master data operations:

// Get dimension members with properties
var members = PlanningModel_1.getMembers("CostCenter");

// Create new members
PlanningModel_1.createMembers("CostCenter", [
    {id: "CC100", description: "Marketing"}
]);

// Update existing members
PlanningModel_1.updateMembers("CostCenter", [
    {id: "CC100", description: "Marketing Dept"}
]);

// Delete members
PlanningModel_1.deleteMembers("CostCenter", ["CC100"]);

DataSource API - Filtering and querying:

// Set dimension filter
Table_1.getDataSource().setDimensionFilter("Version",
    "[Version].[parentId].&[public.Actual]");

// Get members with booked values only
var members = Table_1.getDataSource().getMembers("Account",
    {accessMode: MemberAccessMode.BookedValues});

// Remove filter
Table_1.getDataSource().removeDimensionFilter("Version");

Reference: See references/api-reference.md for complete API documentation.


Data Actions

Data actions perform calculations and data manipulation on planning models.

Step Types

Step TypePurpose
CopyMove data between dimensions/versions
Advanced FormulaComplex calculations
AllocationRule-based distribution
Currency ConversionConvert currencies
Embedded Data ActionRun another data action

Creating a Copy Step

Source:
  Version = Actual
  Year = 2024

Target:
  Version = Budget
  Year = 2025

Mapping:
  Account = Account (same)
  CostCenter = CostCenter (same)

Advanced Formula Example

// Calculate forecast = Actual + (Budget - Actual) * 0.5
[Version].[Forecast] = [Version].[Actual] +
    ([Version].[Budget] - [Version].[Actual]) * 0.5

Parameters

Add parameters to make data actions reusable:

  • Member Parameter: Select dimension member
  • Number Parameter: Enter numeric value
  • String Parameter: Enter text (2025+)
  • Datetime Parameter: Select date/time (2025+)

Reference: See references/data-actions.md for complete configuration guide.


Multi Actions

Multi actions orchestrate multiple planning operations across models and versions.

Available Step Types

  1. Data Action Step: Run data action with parameters
  2. Version Management Step: Publish versions
  3. Predictive Step: Run forecasting scenarios
  4. Data Import Step: Import from SAP sources
  5. API Step: Call external HTTP APIs
  6. Data Locking Step: Lock/unlock data slices
  7. PaPM Step: Run Profitability and Performance Management

Example Multi Action Flow

1. Clean target version (Data Action)
2. Import actuals (Data Import)
3. Run forecast (Predictive)
4. Calculate allocations (Data Action)
5. Publish to public version (Version Management)
6. Lock published data (Data Locking)

Cross-Model Parameters

When using public dimensions, create cross-model parameters to share values across steps in different models.

Reference: See references/data-actions.md for multi action configuration.


S/4HANA ACDOCP Export

Export native planning data from SAC to SAP S/4HANA's ACDOCP table (central ERP plan data storage).

Architecture

SAC Planning Model → Data Export Service → Cloud Connector → API_PLPACDOCPDATA_SRV → ACDOCP

Prerequisites

RequirementDetails
Legacy ModeMust be enabled on planning model
OData ServiceActivate API_PLPACDOCPDATA_SRV in /IWFND/MAINT_SERVICE
Cloud ConnectorRequired for on-premise S/4HANA

Required Dimensions for Export

  • Version (Plan Category): Only public versions can be exported
  • FiscalYearPeriod: Mandatory in export scope
  • Measure: Only ONE target measure per export job
  • G/L Account: Required for ACDOCP mapping

Export Behavior

  • Exported data overwrites existing data within scope
  • S/4HANA generates delta records for changes
  • Deletions don't propagate: Set values to 0 and re-export to clear ACDOCP data
  • Filters cannot be changed after export job creation—name jobs descriptively

Quick Setup

  1. Enable Legacy Mode on planning model
  2. Create S/4HANA connection with Cloud Connector
  3. Data Management → Create Data Export Job
  4. Map dimensions to ACDOCP fields
  5. Define export scope (FiscalYearPeriod + PlanningCategory mandatory)
  6. Schedule or run export

Reference: See references/s4hana-acdocp-export.md for complete configuration guide, troubleshooting, and SAP documentation links.


Seamless Planning with Datasphere

Seamless Planning unifies SAC planning with SAP Datasphere, enabling enterprise-grade storage and governance for plan data.

Architecture Overview

SAC (Planning Logic & UX) ──Direct Persistence──► Datasphere (Data Storage & Governance)

What stays in SAC: Planning calculations, version management, data actions, calendar workflows What moves to Datasphere: Fact data, public dimensions, physical storage, data governance

Key Benefits

BenefitDescription
Unified DataCentralized storage ensures consistency
Direct PersistenceChanges in SAC instantly reflect in Datasphere
Optimized ResourcesReduces SAC memory and storage footprint
Enterprise ReusabilityDatasphere modeling extends to planning data

Prerequisites

  1. SAC tenant on SAP HANA Cloud - Verify in System → About
  2. Co-located tenants - Same SAP data center region
  3. 1:1 tenant linkage - One SAC tenant to one Datasphere tenant
  4. Consistent IdP - Same SAML identity provider
  5. Datasphere space roles - DW Modeler, DW Integrator, or DW Space Administrator

Quick Setup

  1. Create new Planning Model
  2. Select SAP Datasphere Space as Data Storage Location
  3. Configure dimensions (public dimensions stored in Datasphere)
  4. Enable Expose to Datasphere in Model Details
  5. Plan normally in SAC - changes persist automatically

Cross-Model Planning

All models for cross-model operations (data actions, multi actions) must be in the same Datasphere space.

Reference: See references/seamless-planning-datasphere.md for detailed architecture, configuration, and troubleshooting.


BPC Live Connection

SAC supports live data connections to BPC Embedded on S/4HANA, enabling planning with the BPC engine while using SAC's modern interface.

Supported BPC Versions

VersionPlanning Support
BPC Embedded (S/4HANA)Full planning features
BPC for NetWeaverLimited (read-only)
BPC StandardExport to BPC required

Planning Features via BPC Live

  • Data Entry: Direct input to BPC models
  • Planning Sequences: Execute FOX scripts from SAC
  • Version Management: BPC-controlled categories
  • Master Data Planning: Update dimension properties
  • Data Locking: BPC locks integration

Running BPC Planning Sequences

// Execute BPC planning sequence
PlanningSequence_1.setParameterValue("FISCAL_YEAR", "2025");
PlanningSequence_1.setParameterValue("VERSION", "PLAN");
PlanningSequence_1.execute().then(function() {
    Table_1.getDataSource().refreshData();
});

When to Use BPC Live vs Native SAC

Use BPC Live when: Existing BPC investment, complex FOX scripts, integrated with BW reporting Use Native SAC when: New implementation, simpler requirements, mobile-first applications

Reference: See references/bpc-live-connection.md for setup, prerequisites, and troubleshooting.


Value Driver Trees

Value Driver Trees (VDT) visualize how values flow through a planning model, enabling driver-based planning and what-if analysis.

Use Cases

ScenarioExample
Driver-Based PlanningModel how prices, headcount impact revenue
What-If AnalysisSimulate scenarios, see cascading effects
Strategic PlanningVisualize value chain impacts
Executive PresentationsTouchscreen-friendly boardroom displays

Creating a Value Driver Tree

  1. Add Value Driver Tree widget to story or application
  2. Select planning model with Date dimension
  3. Add nodes (auto-create from model or manual)
  4. Configure measures and structures per node
  5. Link nodes (drivers right, outcomes left)
  6. Set presentation date range

Node Configuration

SetupDescription
1 Account + 1 StructureSingle row of values
Multiple AccountsRow per account (e.g., sales + quantity)
Multiple StructuresCompare scenarios/currencies

JavaScript API

// Get VDT reference
var vdt = ValueDriverTree_1;

// Get selected node value
var value = vdt.getSelectedNode().getValue("Revenue", "2025Q1");

// Collapse/expand nodes
vdt.collapseNode("Node_Revenue");
vdt.expandNode("Node_Revenue");

Reference: See references/value-driver-trees.md for detailed setup and best practices.


Data Action Tracing

Data Action Tracing is a debugging tool for inspecting intermediate results during data action execution.

When to Use Tracing

ScenarioHow Tracing Helps
New DevelopmentValidate each step produces expected results
Debugging FailuresIdentify which step causes incorrect data
Performance InvestigationSee which steps process most data
Allocation DebuggingValidate driver ratios and distributions

Adding Tracepoints

  1. Open data action in Data Action Designer
  2. Navigate to step where you want to trace
  3. Click Add Tracepoint (or right-click → Add Tracepoint)
  4. Name descriptively (e.g., "After Copy Step", "Before Allocation")

Running Trace Mode

  1. Open data action in designer
  2. Click Run with Tracing
  3. Set required parameters
  4. Execute - data captured at each tracepoint
  5. Review results in Tracing Results Panel

Analyzing Results

ViewDescription
Data at TracepointAll values at that point
Changes Since PreviousDelta between tracepoints
Filtered ViewFocus on specific data

TRACE() in Advanced Formulas

// Add tracepoints in script
[Revenue] = [Quantity] * [Price]
TRACE("After_Revenue_Calc")

[Final] = [Revenue] * (1 + [Tax])
TRACE("After_Tax")

Reference: See references/data-action-tracing.md for complete debugging guide.


Planning Workflows (Calendar)

The SAP Analytics Cloud calendar organizes collaborative planning processes.

Task Types

General Task: Data entry by assignees

  • Attach work file (story/application)
  • Set due dates and notifications
  • Track completion status

Review Task: Approval workflow

  • Review results of general tasks
  • Approve or reject submissions
  • Automatic notification on status change

Composite Task: Combined entry and review

  • Simplified approval for single-level workflows
  • Driving dimension support for regional planning

Data Locking Task: Schedule lock changes

  • Specify data slice to lock/unlock
  • Set target lock state
  • Event-based triggering

Multi-Level Approval

Round 1: Regional Managers review regional plans
    ↓ (on approval)
Round 2: Finance Director reviews consolidated plan
    ↓ (on approval)
Round 3: CFO final approval
    ↓ (on approval)
Data Locking: Lock approved plan data

Task Dependencies

Configure predecessor tasks to create sequential workflows:

  • Review tasks automatically start when predecessor completes
  • Data locking tasks trigger on approval events

Reference: See references/planning-workflows.md for calendar configuration.


Spreading & Distribution

Spreading (Vertical)

Distributes values from parent to child members:

  • Equal Spread: Divide equally among children
  • Proportional Spread: Maintain existing ratios
  • Automatic: SAC determines best method
// Spreading happens automatically when entering at aggregate level
// Example: Enter 1000 at "Total Regions" spreads to child regions

Distribution (Horizontal)

Moves values between members at same hierarchy level:

  • Select source and target cells
  • Choose distribution method
  • Apply via context menu or script

Allocation by Rules

Configure structured allocations in data actions:

  • Define driver accounts for percentage distribution
  • Set allocation targets
  • Execute via data action or multi action

Data Locking

Protect planning data during and after planning cycles.

Lock States

StateData EntryOwner Can Edit
OpenYesYes
RestrictedNo (except owner)Yes
LockedNoNo
MixedVariesVaries (selection contains multiple states)

Configuration

  1. Enable Data Locking on planning model
  2. Define Driving Dimensions (e.g., Region, Version)
  3. Assign Owners to data slices
  4. Configure Lock Regions via model settings

Script Example

// Get data locking object
var dataLocking = Table_1.getPlanning().getDataLocking();

// Get lock state for selection
var selection = Table_1.getSelections()[0];
var lockState = dataLocking.getState(selection);

// Check if locked
if (lockState === DataLockingState.Locked) {
    Application.showMessage("This data is locked.");
}

Reference: See references/planning-workflows.md for data locking patterns.


Members on the Fly

Create, update, and delete dimension members dynamically at runtime.

Supported Operations

// Create new member
PlanningModel_1.createMembers("CostCenter", {
    id: "CC_NEW",
    description: "New Cost Center"
});

// Update existing member
PlanningModel_1.updateMembers("CostCenter", {
    id: "CC_NEW",
    description: "Updated Description"
});

// Get single member
var member = PlanningModel_1.getMember("CostCenter", "CC_NEW");

// Get members with pagination
var members = PlanningModel_1.getMembers("CostCenter", {
    offset: "0",
    limit: "100"
});

Important Restrictions

  • Dimension Type: Only "Generic" dimensions supported (NOT Account, Version, Time, Organization)
  • Refresh Required: Call Application.refreshData() after member changes
  • Custom Properties: Use prefixes to avoid naming conflicts (e.g., "CUSTOM_Region")

Reference: See references/analytics-designer-planning.md for complete API documentation.


Common JavaScript Patterns

Finding Active Version by Attribute

var allVersions = PlanningModel_1.getMembers("Version");
var activeVersion = "";

for (var i = 0; i < allVersions.length; i++) {
    if (allVersions[i].properties.Active === "X") {
        activeVersion = allVersions[i].id;
        break;
    }
}
console.log("Active Version: " + activeVersion);

Setting Filter from Planning Cycle

Application.showBusyIndicator();
Table_1.setVisible(false);

// Find active planning cycle
var cycles = PlanningModel_1.getMembers("PlanningCycle");
var activeCycle = "";

for (var i = 0; i < cycles.length; i++) {
    if (cycles[i].properties.Flag === "ACTIVE") {
        activeCycle = cycles[i].id;
        break;
    }
}

// Apply MDX filter
Table_1.getDataSource().setDimensionFilter("Date",
    "[Date].[YQM].&[" + activeCycle + "]");

Table_1.setVisible(true);
Application.hideBusyIndicator();

Version Publishing

// Get forecast version
var forecastVersion = Table_1.getPlanning().getPublicVersion("Forecast2025");

// Check if changes need publishing
if (forecastVersion.isDirty()) {
    forecastVersion.publish();
    Application.showMessage("Version published successfully.");
}

Data Action Execution

// Execute data action with parameters
DataAction_1.setParameterValue("Version", "Budget");
DataAction_1.setParameterValue("Year", "2025");

DataAction_1.execute();

// Or execute in background
DataAction_1.executeInBackground();

Reference: See references/javascript-patterns.md for more examples.


Performance Best Practices

Data Action Optimization

  1. Use Input Controls: Link to parameters to reduce data scope
  2. Embed Related Actions: Combine actions on same model/version
  3. Minimize Cross-Model Operations: Keep data in single model when possible
  4. Use Batch Processing: Group operations in single transaction

Story Performance

  1. Enable Data Locking Selectively: Only on models that need it
  2. Use Growing Mode: For large tables with pagination
  3. Limit Visible Dimensions: Reduce data cells displayed
  4. Optimize Filters: Apply story filters before data entry

API Performance

  1. Use Booked Values Filter: Retrieve only posted data
  2. Limit getMembers() Results: Set limit parameter
  3. Cache Member Lists: Store in script variables when reusing
  4. Use Busy Indicator: Improve perceived performance

Troubleshooting

Issue: Data not saving

Check:

  1. Planning enabled on table?
  2. User has planning permissions?
  3. Data locked?
  4. Validation rules failing?

Debug:

console.log("Planning enabled: " + Table_1.getPlanning().isEnabled());
var lockState = Table_1.getPlanning().getDataLocking().getState(selection);
console.log("Lock state: " + lockState);

Issue: Version not publishing

Check:

  1. Valid changes only? (Invalid changes discarded)
  2. Data access control allowing write?
  3. Version not already published?

Issue: Data action failing

Check:

  1. Source data exists?
  2. Target version writable?
  3. Dimension mappings correct?
  4. Parameters set correctly?

Debug: Use data action tracing table with "Show Only Leaves" option.

Issue: getMembers() returns empty

Check:

  1. Dimension name correct?
  2. Model connected?
  3. User has read access?
  4. Using correct API (PlanningModel vs DataSource)?

Official Documentation Links

Essential Resources:

Planning Model & Data:

Data Actions & Multi Actions:

Version Management:

Data Locking:

Calendar & Workflows:

Allocations & Spreading:

Learning Resources:


Bundled Reference Files

This skill includes comprehensive reference documentation (24 files):

API & Scripting:

  1. references/api-reference.md: Complete Analytics Designer API for planning
  2. references/analytics-designer-planning.md: Planning scripting, setUserInput, versions, data locking, members on the fly
  3. references/api-snippets.md: Quick API code examples and snippets

Core Planning Features: 4. references/data-actions.md: Data Actions, Multi Actions, parameters, steps 5. references/multi-actions.md: Orchestrate multiple planning operations 6. references/allocations.md: Rule-based distribution and allocations 7. references/advanced-formulas.md: Complex calculations and formulas 8. references/predictive-conversion.md: Predictive forecasting integration

Workflow & Collaboration: 9. references/planning-workflows.md: Calendar, tasks, approvals, data locking 10. references/scheduling-calendar.md: Planning calendar setup 11. references/input-tasks.md: Collaborative data entry tasks 12. references/job-monitoring.md: Track data action execution

Version Management: 13. references/version-management.md: Versions, publishing, sharing, edit mode 14. references/version-edit-modes.md: Version editing workflows 15. references/version-publishing-notes.md: Publishing best practices

Integration & Advanced: 16. references/s4hana-acdocp-export.md: S/4HANA integration, ACDOCP export, OData setup 17. references/ai-planning-analytics.md: AI-powered planning features

Development: 18. references/javascript-patterns.md: Code snippets, patterns, best practices 19. references/modeling-basics.md: Planning model fundamentals 20. references/data-locking.md: Configure and manage data locks

New in 2025: 21. references/seamless-planning-datasphere.md: Seamless Planning architecture, prerequisites, configuration with SAP Datasphere 22. references/bpc-live-connection.md: BPC Embedded live connection, planning sequences, master data planning 23. references/value-driver-trees.md: Value driver tree setup, node configuration, JavaScript API 24. references/data-action-tracing.md: Data action tracing, tracepoints, debugging techniques


Instructions for Claude

When using this skill:

  1. Check model type first - Ensure planning model (not analytic) for write operations
  2. Verify planning enabled - Table must have planning enabled
  3. Use appropriate API - PlanningModel for master data, getPlanning() for transactions
  4. Handle versions correctly - Private for drafts, publish to public when ready
  5. Respect data locking - Check lock state before suggesting edits
  6. Use busy indicators - For long operations to improve UX
  7. Follow MDX syntax - For dimension filters: [Dim].[Hierarchy].&[Member]
  8. Test data actions - Use tracing before production deployment
  9. Consider performance - Apply filters to reduce data scope
  10. Link to documentation - Include relevant SAP Help links in responses

For troubleshooting:

  • Check console for script errors
  • Verify model connectivity
  • Review data action logs
  • Test with simplified scenarios first
  • Check user permissions and data access

Bundled Resources

Reference Documentation

  • references/data-actions.md - Data actions configuration and execution
  • references/multi-actions.md - Multi-action orchestration
  • references/allocations.md - Allocation methods and spreading
  • references/scheduling-calendar.md - Workflow scheduling
  • references/data-locking.md - Data locking configuration
  • references/version-management.md - Version management best practices
  • references/api-reference.md - Planning API reference
  • references/javascript-patterns.md - JavaScript scripting patterns

Templates

  • templates/data-action-checklist.md - Data action implementation checklist
  • templates/multi-action-checklist.md - Multi-action setup guide
  • templates/parameter-table.md - Parameter table template

License: GPL-3.0 Version: 1.4.0 Maintained by: E.J. Repository: https://github.com/secondsky/sap-skills

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

35.04%
按下载量换算139

Claude

31.87%
按下载量换算126

Cursor

19.39%
按下载量换算77

Gemini CLI

9.62%
按下载量换算38

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。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

继续浏览同类 Skills