| name | data360-connect |
| description | Salesforce Data Cloud Connect phase. Use this skill when the user manages Data Cloud connections, connectors, or sets up a new source system. TRIGGER when: user manages Data Cloud connections, connectors, connector metadata, tests a connection, browses source objects or databases, or sets up a new source system. DO NOT TRIGGER when: the task is about data streams or DLOs (use data360-prepare), DMOs or identity resolution (use data360-harmonize), retrieval/search (use data360-query), or STDM telemetry (use agentforce-observe). |
| compatibility | Requires the sf data360 CLI plugin and a Data Cloud-enabled org |
| metadata | {"version":"1.0"} |
data360-connect: 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 data360-connect 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:
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
Core Operating Rules
- Verify the plugin runtime first; see ../data360-orchestrate/references/plugin-setup.md.
- Run the shared readiness classifier before mutating connections:
node ../data360-orchestrate/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.
Recommended Workflow
1. Classify readiness for connect work
node ../data360-orchestrate/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.jsonexamples/connections/redshift.jsonexamples/connections/sharepoint-unstructured.jsonexamples/connections/snowflake-connection.jsonexamples/connections/ingest-api-connection.jsonexamples/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>
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.
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>
References
