sf-datacloud-connect
Salesforce Data Cloud Connect phase. 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 sf-datacloud-prepare), DMOs or identity resolution (use sf-datacloud-harmonize), retrieval/search (use sf-datacloud-retrieve), or STDM telemetry (use sf-ai-agentforce-observability).
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-connect- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads sf-datacloud-connect automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
sf-datacloud-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 sf-datacloud-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:
- creating data streams or DLOs → sf-datacloud-prepare
- creating DMOs, mappings, IR rulesets, or data graphs → sf-datacloud-harmonize
- writing Data Cloud SQL or search-index workflows → sf-datacloud-retrieve
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 ../sf-datacloud/references/plugin-setup.md.
- Run the shared readiness classifier before mutating connections:
node ~/.claude/skills/sf-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/nullfor standard usage. - Remember that
connection listrequires--connector-type. - For
connection test, pass--connector-typewhen 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 ~/.claude/skills/sf-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.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 listhas 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 testmay need--connector-typefor 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, andtokenEndpointin thecredentialsarray and does not require aparametersarray. - 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-upserthas 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
- 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
- ../sf-datacloud/references/plugin-setup.md
- ../sf-datacloud/references/feature-readiness.md
- ../sf-datacloud/UPSTREAM.md
FAQ
What does the sf-datacloud-connect skill do?
Salesforce Data Cloud Connect phase. 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 sf-datacloud-prepare), DMOs or identity resolution (use sf-datacloud-harmonize), retrieval/search (use sf-datacloud-retrieve), or STDM telemetry (use sf-ai-agentforce-observability).
How do I install sf-datacloud-connect?
Run npx skills add https://github.com/jaganpro/sf-skills --skill sf-datacloud-connect in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/sf-datacloud-connect/ (personal) or .claude/skills/sf-datacloud-connect/ (project).
Which AI agents can use sf-datacloud-connect?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is sf-datacloud-connect safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains sf-datacloud-connect?
It is published by jaganpro in jaganpro/sf-skills. It has 980 recorded installs.
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