sf-flow: Salesforce Flow Creation and Validation

Use this skill when the user needs Flow design or Flow XML work: record-triggered, screen, autolaunched, scheduled, or platform-event Flows, including validation, architecture choices, and safe deployment sequencing.

When This Skill Owns the Task

Use sf-flow when the work involves:

.flow-meta.xml files
Flow Builder architecture and XML generation
record-triggered, screen, scheduled, autolaunched, or platform-event flows
Flow-specific bulk safety, fault paths, and subflow orchestration

Delegate elsewhere when the user is:

writing Apex-first automation → sf-apex
creating objects / fields first → sf-metadata
deploying metadata → sf-deploy
seeding post-deploy test data → sf-data

Required Context to Gather First

Ask for or infer:

flow type
trigger object / entry conditions
core business goal
whether this is new, refactor, or repair
target org alias if deployment or validation is needed
whether related objects / fields already exist

Recommended Workflow

1. Choose the right automation tool

Before building, confirm Flow is the right answer rather than:

formula field
validation rule
roll-up summary
Apex

2. Choose the right Flow type

Need	Default flow type
same-record update before save	before-save record-triggered
related-record work / emails / callouts	after-save record-triggered
guided UI	screen flow
reusable background logic	autolaunched / subflow
scheduled processing	scheduled flow
event-driven declarative response	platform-event flow

3. Start from a template

Prefer the provided assets:

assets/record-triggered-before-save.xml
assets/record-triggered-after-save.xml
assets/screen-flow-template.xml
assets/autolaunched-flow-template.xml
assets/scheduled-flow-template.xml
assets/platform-event-flow-template.xml
assets/subflows/

4. Validate against Flow guardrails

Focus on:

no DML in loops
no Get Records inside loops
proper fault paths
correct trigger conditions
safe subflow composition

5. Hand off deployment and testing

Use:

sf-deploy for deploy / dry-run
sf-data for high-volume test data

High-Signal Rules

Flow architecture

before-save for same-record field updates
after-save for related records, emails, and callouts
do not loop over $Record
use subflows when logic becomes wide or repetitive

Bulk safety

no DML in loops
no Get Records in loops
test with 251+ records when bulk behavior matters
prefer Transform when the job is shaping data, not per-record branching

Error handling

every data-changing path should have fault handling
avoid self-referencing fault connectors
deploy Flows as Draft first when activation risk is non-trivial

Output Format

When finishing, report in this order:

Flow type and goal
Files created or updated
Architecture choices
Bulk/error-handling notes
Deploy/testing next steps

Suggested shape:

Flow: <name>
Type: <flow type>
Files: <paths>
Design: <trigger choice, subflows, key decisions>
Risks: <bulk safety, fault paths, dependencies>
Next step: <dry-run deploy, activate, or test>

Cross-Skill Integration

Need	Delegate to	Reason
create objects / fields first	sf-metadata	schema readiness
deploy / activate flow	sf-deploy	safe deployment sequence
create realistic bulk test data	sf-data	post-deploy verification
create Apex actions / invocables	sf-apex	imperative logic
embed LWC in a screen flow	sf-lwc	custom UI components
expose Flow to Agentforce	sf-ai-agentscript	agent action orchestration

Reference Map

Start here

Design / orchestration

Screen / integration / troubleshooting

Score Guide

Score	Meaning
88+	production-ready Flow
75–87	good Flow with some review items
60–74	functional but needs stronger guardrails
< 60	unsafe / incomplete for deployment