afv-library/skills/orchestrating-datacloud
2026-06-16 06:34:27 +00:00
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assets/definitions feat: @W-22444026@ Introducing Core Skills, Datacloud Skills, Industries and Utility Skills. (#268) 2026-05-14 19:32:15 +05:30
references feat: @W-22444026@ Introducing Core Skills, Datacloud Skills, Industries and Utility Skills. (#268) 2026-05-14 19:32:15 +05:30
scripts feat: @W-22444026@ Introducing Core Skills, Datacloud Skills, Industries and Utility Skills. (#268) 2026-05-14 19:32:15 +05:30
CREDITS.md feat: @W-22444026@ Introducing Core Skills, Datacloud Skills, Industries and Utility Skills. (#268) 2026-05-14 19:32:15 +05:30
README.md feat: @W-22444026@ Introducing Core Skills, Datacloud Skills, Industries and Utility Skills. (#268) 2026-05-14 19:32:15 +05:30
SKILL.md feat: Update LICENSE for sf-skills @W-22832966@ 2026-06-16 06:34:27 +00:00
UPSTREAM.md feat: @W-22444026@ Introducing Core Skills, Datacloud Skills, Industries and Utility Skills. (#268) 2026-05-14 19:32:15 +05:30

orchestrating-datacloud

Salesforce Data Cloud skill family for sf-skills. This is the cross-phase orchestrator for community-driven Data Cloud workflows built around the external sf data360 CLI runtime.

What this skill is for

Use orchestrating-datacloud when the task spans multiple Data Cloud phases:

  • connection + ingestion + harmonization setup
  • troubleshooting a Data Cloud pipeline end to end
  • managing data spaces or data kits
  • deciding which specialized Data Cloud skill to use next

What this skill is not

  • It does not vendor or fork the external Data Cloud CLI plugin.
  • It does not use MCP.
  • It does not replace phase-specific skills once the problem is localized.
  • It does not cover STDM/session tracing/parquet analysis; use observing-agentforce for that.

Data Cloud skill family

Skill Purpose
orchestrating-datacloud Orchestrator, data spaces, data kits, cross-phase workflows
connecting-datacloud Connections, connectors, source discovery
preparing-datacloud Data streams, DLOs, transforms, DocAI
harmonizing-datacloud DMOs, mappings, identity resolution, data graphs
segmenting-datacloud Segments, calculated insights
activating-datacloud Activations, activation targets, data actions
retrieving-datacloud SQL, async query, vector search, search indexes

Runtime model

This family assumes:

  • Salesforce CLI (sf)
  • a Data Cloud-enabled org
  • the external community sf data360 plugin linked into sf

See references/plugin-setup.md.

Deterministic helpers included

Path Purpose
scripts/bootstrap-plugin.sh Clone/update the community plugin, compile it, and link it into sf
scripts/verify-plugin.sh Check that the runtime is available before starting Data Cloud work
scripts/diagnose-org.mjs Classify org readiness by phase before mutating Data Cloud assets
references/feature-readiness.md Map high-signal errors and feature gates to concrete next steps
assets/definitions/ Generic JSON templates for repeatable Data Cloud definition files
UPSTREAM.md Upstream mapping for future distillation and maintenance

Generic templates

The family includes reusable starting points for:

  • data streams
  • DMOs
  • mappings
  • identity resolution rulesets
  • segments
  • search indexes

These are intentionally generic and should be adapted to the target org.

Quick start

The script examples below assume the skill is installed under ~/.claude/skills/ via the full Claude Code installer. If you are working from a repo checkout, run the same scripts from that checkout path.

1. Verify the runtime

bash ~/.claude/skills/orchestrating-datacloud/scripts/verify-plugin.sh
# or with an org alias
bash ~/.claude/skills/orchestrating-datacloud/scripts/verify-plugin.sh myorg

The helper treats sf data360 doctor as advisory and falls back to additional read-only smoke checks when an org is only partially provisioned.

2. Diagnose feature readiness before mutating

node ~/.claude/skills/orchestrating-datacloud/scripts/diagnose-org.mjs -o myorg --json
# optional retrieve-plane probe, only when you know the table is real
node ~/.claude/skills/orchestrating-datacloud/scripts/diagnose-org.mjs -o myorg --phase retrieve --describe-table MyDMO__dlm --json

Use the diagnose helper to distinguish between:

  • feature-gated modules
  • empty-but-enabled modules
  • query-plane issues
  • runtime/auth problems

3. Bootstrap the plugin if needed

python3 ~/.claude/sf-skills-install.py --with-datacloud-runtime
# or run the helper script directly
bash ~/.claude/skills/orchestrating-datacloud/scripts/bootstrap-plugin.sh

4. Start with read-only inspection

sf data360 man
sf data360 doctor -o myorg 2>/dev/null
sf data360 dmo list -o myorg 2>/dev/null
sf data360 segment list -o myorg 2>/dev/null
sf data360 activation platforms -o myorg 2>/dev/null

Common examples

"Set up a Customer 360 proof of concept in Data Cloud"
"Troubleshoot why my unified profiles are not increasing"
"I need to figure out whether this issue is in mappings, identity resolution, or segment SQL"
"Show me how to inspect data spaces and data kits for this org"

References

Primary contributor

Gnanasekaran Thoppae — primary contributor for the orchestrating-datacloud family.