- Skill ID
- jaganpro/sf-skills/sf-industry-commoncore-integration-procedure
- Publisher
- jaganpro
- Repository
- sf-skills
- Installs
- 0
- Files
- 8
- License
- MIT
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
jaganpro/sf-skills/sf-industry-commoncore-integration-procedureInstalls these files- CREDITS.md
- LICENSE
- SKILL.md
- assets/omni-process-element-dr-extract.json
- assets/omni-process-element-set-values.json
- assets/omni-process-ip.json
- references/best-practices.md
- references/element-types.md
What this skill tells the agent
sf-industry-commoncore-integration-procedure: OmniStudio Integration Procedure Creation and Validation
Expert OmniStudio Integration Procedure (IP) builder with deep knowledge of server-side process orchestration. Create production-ready IPs that combine DataRaptor/Data Mapper actions, Apex Remote Actions, HTTP callouts, conditional logic, and nested procedure calls into declarative multi-step operations.
Quick Reference
Scoring: 110 points across 6 categories. Thresholds: ✅ 90+ (Deploy) | ⚠️ 67-89 (Review) | ❌ <67 (Block - fix required)
Core Responsibilities
- IP Generation: Create well-structured Integration Procedures from requirements, selecting correct element types and wiring inputs/outputs
- Element Composition: Assemble DataRaptor actions, Remote Actions, HTTP callouts, conditional blocks, loops, and nested IP calls into coherent orchestrations
- Dependency Analysis: Validate that referenced DataRaptors, Apex classes, and nested IPs exist and are active before deployment
- Error Handling: Enforce try/catch patterns, conditional rollback, and response validation across all data-modifying steps
CRITICAL: Orchestration Order
sf-industry-commoncore-omnistudio-analyze -> sf-industry-commoncore-datamapper -> sf-industry-commoncore-integration-procedure -> sf-industry-commoncore-omniscript -> sf-industry-commoncore-flexcard (you are here: sf-industry-commoncore-integration-procedure)
Data Mappers referenced by the IP must exist FIRST. Build and deploy DataRaptors/Data Mappers before the IP that calls them. The IP must be active before any OmniScript or FlexCard can invoke it.
Key Insights
| Insight | Details |
|---|---|
| Chaining | IPs call other IPs via Integration Procedure Action elements. Output of one step feeds input of the next via response mapping. Design data flow linearly where possible. |
| Response Mapping | Each element's output is namespaced under its element name in the response JSON. Use %elementName:keyPath% syntax to reference upstream outputs in downstream inputs. |
| Caching | IPs support platform cache for read-heavy orchestrations. Set cacheType and cacheTTL in the procedure's PropertySet. Avoid caching procedures that perform DML. |
| Versioning | Type/SubType pairs uniquely identify an IP. Use SubType for versioning (e.g., Type=AccountOnboarding, SubType=v2). Only one version can be active at a time per Type/SubType. |
Core Namespace Discriminator: OmniStudio Core stores both Integration Procedures and OmniScripts in the OmniProcess table. Use IsIntegrationProcedure = true or OmniProcessType = 'Integration Procedure' to filter IPs. Without a filter, queries return mixed results.
CRITICAL — Creating IPs via Data API: When creating OmniProcess records, setIsIntegrationProcedure = trueto make the record an Integration Procedure. TheOmniProcessTypepicklist is computed from this boolean and cannot be set directly. Also,Nameis a required field onOmniProcess(not documented in standard OmniStudio docs). Usesf api request rest --method POST --body @file.jsonfor creation — thesf data create record --valuesflag cannot handle JSON textarea fields likePropertySetConfig.
Workflow Design (5-Phase Pattern)
Phase 1: Requirements Gathering
Before building, evaluate alternatives: Sometimes a single DataRaptor, an Apex service, or a Flow is the better choice. IPs are optimal when you need declarative multi-step orchestration with branching, error handling, and mixed data sources.
Ask the user to gather:
- Purpose and business process being orchestrated
- Target objects and data sources (Salesforce objects, external APIs, or both)
- Type/SubType naming (e.g.,
Type=OrderProcessing,SubType=Standard) - Target org alias for deployment
Then: Check existing IPs via CLI query (see CLI Commands below), identify reusable DataRaptors/Data Mappers, and review dependent components with sf-industry-commoncore-omnistudio-analyze.
Phase 2: Design & Element Selection
| Element Type | Use Case | PropertySet Key |
|---|---|---|
| DataRaptor Extract Action | Read Salesforce data | bundle |
| DataRaptor Load Action | Write Salesforce data | bundle |
| DataRaptor Transform Action | Data shaping/mapping | bundle |
| Remote Action | Call Apex class method | remoteClass, remoteMethod |
| Integration Procedure Action | Call nested IP | ipMethod (format: Type_SubType) |
| HTTP Action | External API callout | path, method |
| Conditional Block | Branching logic | -- |
| Loop Block | Iterate over collections | -- |
| Set Values | Assign variables/constants | -- |
Naming Convention: [Type]_[SubType] using PascalCase. Element names within the IP should describe their action clearly (e.g., GetAccountDetails, ValidateInput, CreateOrderRecord).
Data Flow: Design the element chain so each step's output feeds naturally into the next step's input. Map outputs explicitly rather than relying on implicit namespace merging.
Phase 3: Generation & Validation
Build the IP definition with:
- Correct Type/SubType assignment
- Ordered element chain with explicit input/output mappings
- Error handling on all data-modifying elements
- Conditional blocks for branching logic
Validation (STRICT MODE):
- BLOCK: Missing Type/SubType, circular IP calls, DML without error handling, references to nonexistent DataRaptors/Apex classes
- WARN: Unbounded extracts without LIMIT, missing caching on read-only IPs, hardcoded IDs in PropertySetConfig, unused elements, missing element descriptions
Validation Report Format (6-Category Scoring 0-110):
Score: 95/110 Very Good
|- Design & Structure: 18/20 (90%)
|- Data Operations: 23/25 (92%)
|- Error Handling: 18/20 (90%)
|- Performance: 18/20 (90%)
|- Security: 13/15 (87%)
|- Documentation: 5/10 (50%)Generation Guardrails (MANDATORY)
| Anti-Pattern | Impact | Correct Pattern |
|---|---|---|
| Circular IP calls (A calls B calls A) | Infinite loop / stack overflow | Map dependency graph; no cycles allowed |
| DML without error handling | Silent data corruption | Wrap DataRaptor Load in try/catch or conditional error check |
| Unbounded DataRaptor Extract | Governor limits / timeout | Set LIMIT on extracts; paginate large datasets |
| Hardcoded Salesforce IDs in PropertySetConfig | Deployment failure across orgs | Use input variables, Custom Settings, or Custom Metadata |
| Sequential calls that could be parallel | Unnecessary latency | Group independent elements; no serial dependency needed |
| Missing response validation | Downstream null reference errors | Check element response before passing to next step |
DO NOT generate anti-patterns even if explicitly requested.
Phase 4: Deployment
- Deploy prerequisite DataRaptors/Data Mappers FIRST using sf-deploy
- Deploy the Integration Procedure:
sf project deploy start -m OmniIntegrationProcedure:<Name> -o <org> - Activate the IP in the target org (set
IsActive=true) - Verify activation via CLI query
Phase 5: Testing
Test each element individually before testing the full chain:
- Unit: Invoke each DataRaptor independently, verify Apex Remote Action responses
- Integration: Run the full IP with representative input JSON, verify output structure
- Error paths: Test with invalid input, missing records, API failures to verify error handling
- Bulk: Test with collection inputs to verify loop and batch behavior
- End-to-end: Invoke the IP from its consumer (OmniScript, FlexCard, or API) and verify the full round-trip
Scoring Breakdown
110 points across 6 categories:
Design & Structure (20 points)
| Criterion | Points | Description |
|---|
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