omnistudio-datamapper-generate

Name: omnistudio-datamapper-generate
Author: forcedotcom

744stars272forks

How to install omnistudio-datamapper-generate?

forcedotcom/sf-skills/omnistudio-datamapper-generate

$npx -y skills add forcedotcom/sf-skills --skill omnistudio-datamapper-generate

Installs into the current project.

Summary

OmniStudio Data Mapper (formerly DataRaptor) creation and validation with 100-point scoring. Use when building Extract, Transform, Load, or Turbo Extract Data Mappers, mapping Salesforce object fields, or reviewing existing Data Mapper configurations. TRIGGER when: user creates D

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SKILL.md

1	# omnistudio-datamapper-generate: OmniStudio Data Mapper Creation and Validation
2
3	Expert OmniStudio Data Mapper developer specializing in Extract, Transform, Load, and Turbo Extract configurations. Generate production-ready, performant, and maintainable Data Mapper definitions with proper field mappings, query optimization, and data integrity safeguards.
4
5	---
6
7	## Scope
8
9	- In scope: Creating and validating OmniStudio Data Mapper configurations (Extract, Transform, Load, Turbo Extract); field mapping design; query optimization; FLS (Field-Level Security) validation; deployment via platform-metadata-deploy skill
10	- Out of scope: Building Integration Procedures (use `omnistudio-integration-procedure-generate`), authoring OmniScripts (use `omnistudio-omniscript-generate`), designing FlexCards (use `omnistudio-flexcard-generate`), analyzing cross-component dependencies (use `omnistudio-dependencies-analyze`)
11
12	---
13
14	## Core Responsibilities
15
16	1. Generation: Create Data Mapper configurations (Extract, Transform, Load, Turbo Extract) from requirements
17	2. Field Mapping: Design object-to-output field mappings with proper type handling, lookup resolution, and null safety
18	3. Dependency Tracking: Identify related OmniStudio components (Integration Procedures, OmniScripts, FlexCards) that consume or feed Data Mappers
19	4. Validation & Scoring: Score Data Mapper configurations against 5 categories (0-100 points)
20
21	---
22
23	## CRITICAL: Orchestration Order
24
25	omnistudio-dependencies-analyze -> omnistudio-datamapper-generate -> omnistudio-integration-procedure-generate -> omnistudio-omniscript-generate -> omnistudio-flexcard-generate (you are here: omnistudio-datamapper-generate)
26
27	Data Mappers are the data access layer of the OmniStudio stack. They must be created and deployed before Integration Procedures or OmniScripts that reference them. Use omnistudio-dependencies-analyze FIRST to understand existing component dependencies.
28
29	---
30
31	## Key Insights
32
33	\| Insight \| Details \|
34	\|---------\|---------\|
35	\| Extract vs Turbo Extract \| Extract uses standard SOQL with relationship queries. Turbo Extract uses server-side compiled queries for read-heavy, high-volume scenarios (10x+ faster). Turbo Extract does not support formula fields, related lists, or write operations. \|
36	\| Transform is in-memory \| Transform Data Mappers operate entirely in memory with no DML or SOQL. They reshape data structures between steps in an Integration Procedure. Use for JSON-to-JSON transformations, field renaming, and data flattening. \|
37	\| Load = DML \| Load Data Mappers perform insert, update, upsert, or delete operations. They require proper FLS checks and error handling. Always validate field-level security before deploying Load Data Mappers to production. \|
38	\| OmniDataTransform metadata \| Data Mappers are stored as OmniDataTransform and OmniDataTransformItem records. Retrieve and deploy using these metadata type names, not the legacy DataRaptor API names. \|
39
40	---
41
42	## Workflow (5-Phase Pattern)
43
44	### Phase 1: Requirements Gathering
45
46	Ask the user to gather:
47	- Data Mapper type (Extract, Transform, Load, Turbo Extract)
48	- Target Salesforce object(s) and fields
49	- Target org alias
50	- Consuming component (Integration Procedure, OmniScript, or FlexCard name)
51	- Data volume expectations (record counts, frequency)
52
53	Then:
54	1. Check existing Data Mappers: `Glob: */OmniDataTransform`
55	2. Check existing OmniStudio metadata: `Glob: /omnistudio/`
56	3. Create a task list
57
58	---
59
60	### Phase 2: Design & Type Selection
61
62	\| Type \| Use Case \| Naming Prefix \| Supports DML \| Supports SOQL \|
63	\|------\|----------\|---------------\|--------------\|---------------\|
64	\| Extract \| Read data from one or more objects with relationship queries \| `DR_Extract_` \| No \| Yes \|
65	\| Turbo Extract \| High-volume read-only queries, server-side compiled \| `DR_TurboExtract_` \| No \| Yes (compiled) \|
66	\| Transform \| In-memory data reshaping between procedure steps \| `DR_Transform_` \| No \| No \|
67	\| Load \| Write data (insert, update, upsert, delete) \| `DR_Load_` \| Yes \| No \|
68
69	Naming Format: `[Prefix][Object]_[Purpose]` using PascalCase
70
71	Examples:
72	- `DR_Extract_Account_Details` -- Extract Account with related Contacts
73	- `DR_TurboExtract_Case_L

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omnistudio-datamapper-generate

744stars272forks

View on GitHub

How to install omnistudio-datamapper-generate?

forcedotcom/sf-skills/omnistudio-datamapper-generate

$npx -y skills add forcedotcom/sf-skills --skill omnistudio-datamapper-generate

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# omnistudio-datamapper-generate: OmniStudio Data Mapper Creation and Validation
2
3	Expert OmniStudio Data Mapper developer specializing in Extract, Transform, Load, and Turbo Extract configurations. Generate production-ready, performant, and maintainable Data Mapper definitions with proper field mappings, query optimization, and data integrity safeguards.
4
5	---
6
7	## Scope
8
9	- In scope: Creating and validating OmniStudio Data Mapper configurations (Extract, Transform, Load, Turbo Extract); field mapping design; query optimization; FLS (Field-Level Security) validation; deployment via platform-metadata-deploy skill
10	- Out of scope: Building Integration Procedures (use `omnistudio-integration-procedure-generate`), authoring OmniScripts (use `omnistudio-omniscript-generate`), designing FlexCards (use `omnistudio-flexcard-generate`), analyzing cross-component dependencies (use `omnistudio-dependencies-analyze`)
11
12	---
13
14	## Core Responsibilities
15
16	1. Generation: Create Data Mapper configurations (Extract, Transform, Load, Turbo Extract) from requirements
17	2. Field Mapping: Design object-to-output field mappings with proper type handling, lookup resolution, and null safety
18	3. Dependency Tracking: Identify related OmniStudio components (Integration Procedures, OmniScripts, FlexCards) that consume or feed Data Mappers
19	4. Validation & Scoring: Score Data Mapper configurations against 5 categories (0-100 points)
20
21	---
22
23	## CRITICAL: Orchestration Order
24
25	omnistudio-dependencies-analyze -> omnistudio-datamapper-generate -> omnistudio-integration-procedure-generate -> omnistudio-omniscript-generate -> omnistudio-flexcard-generate (you are here: omnistudio-datamapper-generate)
26
27	Data Mappers are the data access layer of the OmniStudio stack. They must be created and deployed before Integration Procedures or OmniScripts that reference them. Use omnistudio-dependencies-analyze FIRST to understand existing component dependencies.
28
29	---
30
31	## Key Insights
32
33	\| Insight \| Details \|
34	\|---------\|---------\|
35	\| Extract vs Turbo Extract \| Extract uses standard SOQL with relationship queries. Turbo Extract uses server-side compiled queries for read-heavy, high-volume scenarios (10x+ faster). Turbo Extract does not support formula fields, related lists, or write operations. \|
36	\| Transform is in-memory \| Transform Data Mappers operate entirely in memory with no DML or SOQL. They reshape data structures between steps in an Integration Procedure. Use for JSON-to-JSON transformations, field renaming, and data flattening. \|
37	\| Load = DML \| Load Data Mappers perform insert, update, upsert, or delete operations. They require proper FLS checks and error handling. Always validate field-level security before deploying Load Data Mappers to production. \|
38	\| OmniDataTransform metadata \| Data Mappers are stored as OmniDataTransform and OmniDataTransformItem records. Retrieve and deploy using these metadata type names, not the legacy DataRaptor API names. \|
39
40	---
41
42	## Workflow (5-Phase Pattern)
43
44	### Phase 1: Requirements Gathering
45
46	Ask the user to gather:
47	- Data Mapper type (Extract, Transform, Load, Turbo Extract)
48	- Target Salesforce object(s) and fields
49	- Target org alias
50	- Consuming component (Integration Procedure, OmniScript, or FlexCard name)
51	- Data volume expectations (record counts, frequency)
52
53	Then:
54	1. Check existing Data Mappers: `Glob: */OmniDataTransform`
55	2. Check existing OmniStudio metadata: `Glob: /omnistudio/`
56	3. Create a task list
57
58	---
59
60	### Phase 2: Design & Type Selection
61
62	\| Type \| Use Case \| Naming Prefix \| Supports DML \| Supports SOQL \|
63	\|------\|----------\|---------------\|--------------\|---------------\|
64	\| Extract \| Read data from one or more objects with relationship queries \| `DR_Extract_` \| No \| Yes \|
65	\| Turbo Extract \| High-volume read-only queries, server-side compiled \| `DR_TurboExtract_` \| No \| Yes (compiled) \|
66	\| Transform \| In-memory data reshaping between procedure steps \| `DR_Transform_` \| No \| No \|
67	\| Load \| Write data (insert, update, upsert, delete) \| `DR_Load_` \| Yes \| No \|
68
69	Naming Format: `[Prefix][Object]_[Purpose]` using PascalCase
70
71	Examples:
72	- `DR_Extract_Account_Details` -- Extract Account with related Contacts
73	- `DR_TurboExtract_Case_L

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6 picks

Type