Connecting Datacloud

connecting-datacloud: Data Cloud Connect Phase

Use this skill when the user needs source connection work: connector discovery, connection metadata, connection testing, source-object browsing, connector schema inspection, or connector-specific setup payloads for external sources.

When This Skill Owns the Task

Use connecting-datacloud when the work involves:

• sf data360 connection *
• connector catalog inspection
• connection creation, update, test, or delete
• browsing source objects, fields, databases, or schemas
• identifying connector types already in use
• preparing connector definitions for Snowflake, SharePoint Unstructured, or Ingestion API sources

Delegate elsewhere when the user is:

• creating data streams or DLOs → preparing-datacloud
• creating DMOs, mappings, IR rulesets, or data graphs → harmonizing-datacloud
• writing Data Cloud SQL or search-index workflows → retrieving-datacloud

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Required Context to Gather First

Ask for or infer:

• target org alias
• connector type or source system
• whether the user wants inspection only or live mutation
• connection name or ID if one already exists
• whether credentials are already configured outside the CLI
• whether the user also expects stream creation right after connection setup
• whether the source is a database, an unstructured document source, or an Ingestion API feed

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Core Operating Rules

• Verify the plugin runtime first; see ../orchestrating-datacloud/references/plugin-setup.md.
• Run the shared readiness classifier before mutating connections: node ../orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase connect --json.
• Prefer read-only discovery before connection creation.
• Suppress linked-plugin warning noise with 2>/dev/null for standard usage.
• Remember that connection list requires --connector-type.
• For connection test, pass --connector-type when resolving a non-Salesforce connection by name.
• Discover existing connector types from streams first when the org is unfamiliar.
• Use curated example payloads before inventing connector-specific credentials or parameters.
• For connector types outside the curated examples, inspect a known-good UI-created connection via REST before building JSON.
• Do not promise API-based stream creation for every connector type just because connection creation succeeds.

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Recommended Workflow

1. Classify readiness for connect work

node ../orchestrating-datacloud/scripts/diagnose-org.mjs -o <org> --phase connect --json

2. Discover connector types

sf data360 connection connector-list -o <org> 2>/dev/null
sf data360 data-stream list -o <org> 2>/dev/null

3. Inspect connections by type

sf data360 connection list -o <org> --connector-type SalesforceDotCom 2>/dev/null
sf data360 connection list -o <org> --connector-type REDSHIFT 2>/dev/null
sf data360 connection list -o <org> --connector-type SNOWFLAKE 2>/dev/null

4. Inspect a specific connection or uploaded schema

sf data360 connection get -o <org> --name <connection> 2>/dev/null
sf data360 connection objects -o <org> --name <connection> 2>/dev/null
sf data360 connection fields -o <org> --name <connection> 2>/dev/null
sf data360 connection schema-get -o <org> --name <connection-id> 2>/dev/null

5. Test or create only after discovery

sf data360 connection test -o <org> --name <connection> --connector-type <type> 2>/dev/null
sf data360 connection create -o <org> -f connection.json 2>/dev/null

6. Start from curated example payloads for external connectors

Use the phase-owned examples before inventing a payload from scratch:

• examples/connections/heroku-postgres.json
• examples/connections/redshift.json
• examples/connections/sharepoint-unstructured.json
• examples/connections/snowflake-connection.json
• examples/connections/ingest-api-connection.json
• examples/connections/ingest-api-schema.json

Typical Ingestion API setup flow:

sf data360 connection create -o <org> -f examples/connections/ingest-api-connection.json 2>/dev/null
sf data360 connection schema-upsert -o <org> --name <connector-id> -f examples/connections/ingest-api-schema.json 2>/dev/null
sf data360 connection schema-get -o <org> --name <connector-id> 2>/dev/null

7. Discover payload fields for unknown connector types

Create one in the UI, then inspect it directly:

sf api request rest "/services/data/v66.0/ssot/connections/<id>" -o <org>

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High-Signal Gotchas

• connection list has no true global "list all" mode; query by connector type.
• The connector catalog name and connection connector type are not always the same label.
• connection test may need --connector-type for name resolution when the source is not a default Salesforce connector.
• An empty connection list usually means "enabled but not configured yet", not "feature disabled".
• Heroku Postgres, Redshift, Snowflake, SharePoint Unstructured, and Ingestion API all use different credential and parameter shapes; reuse the curated examples instead of guessing.
• SharePoint Unstructured uses clientId, clientSecret, and tokenEndpoint in the credentials array and does not require a parameters array.
• Snowflake uses key-pair auth and can often be created through the API, but downstream stream creation can still remain UI-only.
• Ingestion API connector setup is incomplete until connection schema-upsert has uploaded the object schema.
• Some external connector credential setup still depends on UI-side configuration or external-system permissions.

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Output Format

Connect task: <inspect / create / test / update>
Connector type: <SalesforceDotCom / REDSHIFT / SNOWFLAKE / SPUnstructuredDocument / IngestApi / ...>
Target org: <alias>
Commands: <key commands run>
Verification: <passed / partial / blocked>
Next step: <prepare phase or connector follow-up>

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References

• README.md
• examples/connections/heroku-postgres.json
• examples/connections/redshift.json
• examples/connections/sharepoint-unstructured.json
• examples/connections/snowflake-connection.json
• examples/connections/ingest-api-connection.json
• examples/connections/ingest-api-schema.json
• ../orchestrating-datacloud/references/plugin-setup.md
• ../orchestrating-datacloud/references/feature-readiness.md
• ../orchestrating-datacloud/UPSTREAM.md

Credits & Acknowledgments

This skill is part of the *-datacloud family of skills covering the full Data Cloud workflow lifecycle. Shared upstream source mapping and maintenance notes live in:

• ../orchestrating-datacloud/CREDITS.md
• ../orchestrating-datacloud/UPSTREAM.md

connecting-datacloud

Connection and connector workflows for Salesforce Data Cloud.

Use this skill for

• listing available connector types
• inspecting configured connections
• testing a connection
• browsing source objects, databases, fields, and uploaded schemas
• preparing connector JSON for Snowflake, SharePoint Unstructured, and Ingestion API sources
• preparing for stream creation

Key reminders

• connection list requires --connector-type
• connection test may need --connector-type for non-Salesforce name resolution
• use connection schema-upsert after creating an Ingestion API connector
• start with inspection before mutation
• use 2>/dev/null to suppress linked-plugin warning noise
• some connector types can be created by API while downstream stream creation still requires UI flow

Example requests

"Show me which Data Cloud connections already exist in this org"
"Test my Snowflake Data Cloud connection"
"What source objects are available on this Salesforce connector?"
"Help me create an Ingestion API connector and upload its schema"
"Set up a SharePoint Unstructured connection for document ingestion"

Common commands

sf data360 connection connector-list -o myorg 2>/dev/null
sf data360 connection list -o myorg --connector-type SalesforceDotCom 2>/dev/null
sf data360 connection get -o myorg --name SalesforceDotCom_Home 2>/dev/null
sf data360 connection test -o myorg --name Snowflake_Demo --connector-type SNOWFLAKE 2>/dev/null
sf data360 connection schema-get -o myorg --name <connector-id> 2>/dev/null
sf data360 connection create -o myorg -f examples/connections/heroku-postgres.json 2>/dev/null
sf data360 connection schema-upsert -o myorg --name <connector-id> -f examples/connections/ingest-api-schema.json 2>/dev/null

Example payloads

• examples/connections/heroku-postgres.json
• examples/connections/redshift.json
• examples/connections/sharepoint-unstructured.json
• examples/connections/snowflake-connection.json
• examples/connections/ingest-api-connection.json
• examples/connections/ingest-api-schema.json

References

• SKILL.md
• ../orchestrating-datacloud/references/plugin-setup.md
• ../orchestrating-datacloud/UPSTREAM.md
• CREDITS.md