Generating Flow

Name: Generating Flow
Author: forcedotcom

forcedotcom/afv-library

1.6k installs
763 repo stars
Updated July 24, 2026
forcedotcom/afv-library

This is a copy of generating-flow by forcedotcom - installs and ranking accrue to the original listing.

generating-flow is a Salesforce agent skill that generates complete Flow metadata XML for Screen, Autolaunched, Record-Triggered, and Scheduled automations for developers who need CRM workflows without hand-authoring flo

About

generating-flow is a Salesforce Flow generation skill (manifest version 1.0) from forcedotcom/afv-library that drives a required three-step MCP pipeline: fetchGroundedObjectMetadata, flowElementSelection, and flowElementGeneration. It is the dedicated skill when requests mention creating flows, record-triggered before/after-save logic, daily schedules, field updates on create, or workflow-style automation phrasing. Developers reach for generating-flow instead of writing Flow XML by hand or guessing element shapes. It covers Screen, Autolaunched, Record-Triggered, and Scheduled flow types through execute_metadata_action.

Runs the exact 3-step MCP pipeline: fetchGroundedObjectMetadata → flowElementSelection → flowElementGeneration
Generates Screen, Autolaunched, Record-Triggered (before/after-save), and Scheduled Flows
Triggers on natural language requests such as "when a record is created", "trigger daily at", "send an email when", or "
Returns ready-to-deploy Flow XML metadata
This is the only skill for Salesforce Flow generation

Generating Flow by the numbers

1,571 all-time installs (skills.sh)
+2 installs in the week ending Jul 28, 2026 (Skillselion tracking)
Security screen: LOW risk (skills.sh audit)
Data as of Jul 28, 2026 (Skillselion catalog sync)

npx skills add https://github.com/forcedotcom/afv-library --skill generating-flow

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Installs	1.6k
repo stars	★ 763
Security audit	3 / 3 scanners passed
Last updated	July 24, 2026
Repository	forcedotcom/afv-library ↗

How do you generate Salesforce Flow XML metadata?

Generate complete Salesforce Flow metadata XML for any automation scenario without writing code.

Who is it for?

Salesforce developers automating record triggers, screen flows, or scheduled jobs who want grounded Flow XML from natural-language requirements.

Skip if: Apex-heavy custom logic, non-Salesforce workflow engines, or teams without Salesforce MCP metadata access configured.

When should I use this skill?

User asks to create, build, or generate a Salesforce Flow, including triggers like 'when a record is created' or 'trigger daily at'.

What you get

Complete Salesforce Flow metadata XML ready for deploy via execute_metadata_action.

Flow metadata XML
flow element selections

By the numbers

Manifest version 1.0
Uses a required 3-step MCP metadata pipeline

Files

SKILL.mdMarkdownGitHub ↗

data360-query: Data Cloud Retrieve Phase

Use this skill when the user needs query, search, and metadata introspection for Data Cloud: sync SQL, paginated SQL, async query workflows, table describe, vector search, hybrid search, or search index operations.

When This Skill Owns the Task

Use data360-query when the work involves:

sf data360 query *
sf data360 search-index *
sf data360 metadata *
sf data360 profile * or sf data360 insight * inspection
understanding Data Cloud SQL results or query shape

Delegate elsewhere when the user is:

writing standard CRM SOQL only → platform-soql-query
designing segment or calculated insight assets → data360-segment
analyzing STDM/session tracing/parquet telemetry → agentforce-observe

---

Required Context to Gather First

Ask for or infer:

target org alias
whether the user needs quick count, medium result set, large export, schema inspection, or semantic search
table/index name if known
whether the task is read-only SQL or search-index lifecycle management

---

Core Operating Rules

Treat Data Cloud SQL as its own query language, not SOQL.
Run the shared readiness classifier before relying on query/search surfaces: node ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --json.
Use describe before guessing columns.
Prefer sqlv2 or async query flows for larger result sets.
Use vector search or hybrid search only when the search index lifecycle is healthy.
Keep STDM/parquet/session-tracing workflows out of this skill family.

---

Recommended Workflow

1. Classify readiness for retrieve work

node ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --json
# optional query-plane probe, only with a real table name
node ../data360-orchestrate/scripts/diagnose-org.mjs -o <org> --phase retrieve --describe-table MyDMO__dlm --json

2. Choose the smallest correct query shape

sf data360 query sql -o <org> --sql 'SELECT COUNT(*) FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query sqlv2 -o <org> --sql 'SELECT * FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query async-create -o <org> --sql 'SELECT * FROM "ssot__Individual__dlm"' 2>/dev/null

3. Use describe before guessing fields

sf data360 query describe -o <org> --table ssot__Individual__dlm 2>/dev/null

4. Use vector or hybrid search only when an index exists

sf data360 search-index list -o <org> 2>/dev/null
sf data360 query vector -o <org> --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o <org> --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o <org> --index Insurance_Index --query "weather damage coverage" --prefilter "Type_of_Insurance__c='Home'" --limit 10 2>/dev/null

5. Reuse curated search-index examples when creating indexes

Use the phase-owned examples instead of inventing JSON from scratch:

examples/search-indexes/vector-knowledge.json
examples/search-indexes/hybrid-structured.json

---

High-Signal Gotchas

Data Cloud SQL is not SOQL.
Table names should be double-quoted in SQL.
sqlv2 is better than ad hoc OFFSET paging for medium result sets.
async query is preferable for large results.
search-index operations and vector/hybrid queries depend on the index lifecycle being healthy.
Hybrid search can use --prefilter, but only on fields configured as prefilter-capable when the search index was created.
HNSW index parameters are typically read-only on create; leave userValues: [] unless the platform explicitly documents otherwise.
query describe is not a universal tenant probe; only run it with a known DMO or DLO table after broader readiness has been confirmed.

---

Output Format

Retrieve task: <sql / sqlv2 / async / describe / vector / search-index>
Target org: <alias>
Target object: <table or index>
Commands: <key commands run>
Verification: <query rows / schema / status>
Next step: <segment / harmonize / follow-up>

---

References

README.md
examples/search-indexes/vector-knowledge.json
examples/search-indexes/hybrid-structured.json
../data360-orchestrate/assets/definitions/search-index.template.json
../data360-orchestrate/references/plugin-setup.md
../data360-orchestrate/references/feature-readiness.md

{
  "label": "<INDEX_NAME>",
  "developerName": "<INDEX_NAME>",
  "description": "Hybrid search index on a structured Data Cloud DMO",
  "sourceDmoDeveloperName": "<SOURCE_DMO>__dlm",
  "chunkDmoName": "<INDEX_NAME> chunk",
  "chunkDmoDeveloperName": "<INDEX_NAME>_chunk",
  "vectorDmoName": "<INDEX_NAME> index",
  "vectorDmoDeveloperName": "<INDEX_NAME>_index",
  "searchType": "HYBRID",
  "vectorEmbedding": {
    "vectorEmbeddingRelatedFields": []
  },
  "rankingConfigurations": [],
  "chunkingConfiguration": {
    "fieldLevelConfigurations": [
      {
        "sourceDmoDeveloperName": "<SOURCE_DMO>__dlm",
        "sourceDmoFieldDeveloperName": "<TEXT_FIELD>__c",
        "config": {
          "id": "passage_extraction",
          "userValues": [
            { "id": "max_tokens", "value": "512" },
            { "id": "strip_html", "value": "true" }
          ]
        }
      }
    ]
  },
  "vectorEmbeddingConfiguration": {
    "embeddingModel": {
      "id": "e5_large_v2",
      "userValues": [
        { "id": "dimension", "value": "1024" },
        { "id": "max_token_limit", "value": "512" }
      ]
    },
    "index": {
      "id": "HNSW",
      "userValues": []
    },
    "similarityMetric": "COSINE"
  }
}

{
  "label": "My_kav",
  "developerName": "My_kav",
  "sourceDmoDeveloperName": "ssot__KnowledgeArticleVersion__dlm",
  "chunkDmoName": "My_kav chunk",
  "chunkDmoDeveloperName": "My_kav_chunk",
  "vectorDmoName": "My_kav index",
  "vectorDmoDeveloperName": "My_kav_index",
  "searchType": "VECTOR",
  "vectorEmbedding": {
    "vectorEmbeddingRelatedFields": []
  },
  "chunkingConfiguration": {
    "fieldLevelConfigurations": [
      {
        "sourceDmoDeveloperName": "ssot__KnowledgeArticleVersion__dlm",
        "sourceDmoFieldDeveloperName": "ssot__Name__c",
        "config": {
          "id": "passage_extraction",
          "userValues": [
            { "id": "strip_html", "value": "true" },
            { "id": "max_tokens", "value": "512" }
          ]
        }
      }
    ]
  },
  "vectorEmbeddingConfiguration": {
    "embeddingModel": {
      "id": "e5_large_v2",
      "userValues": [
        { "id": "dimension", "value": "1024" },
        { "id": "max_token_limit", "value": "512" }
      ]
    },
    "index": {
      "id": "HNSW",
      "userValues": []
    },
    "similarityMetric": "COSINE"
  },
  "rankingConfigurations": []
}

data360-query

Query and search workflows for Salesforce Data Cloud.

Use this skill for

quick SQL counts
paginated SQL (sqlv2)
async query lifecycles
table describe
vector search
hybrid search with optional prefilter
search index inspection and lifecycle work

Example requests

"Run a Data Cloud SQL query against unified profiles"
"Describe this Data Cloud table before I write SQL"
"Help me troubleshoot vector search in Data Cloud"
"Run a hybrid search with a prefilter in Data Cloud"
"Create and inspect a search index"

Common commands

sf data360 query sql -o myorg --sql 'SELECT COUNT(*) FROM "ssot__Individual__dlm"' 2>/dev/null
sf data360 query describe -o myorg --table ssot__Individual__dlm 2>/dev/null
sf data360 search-index list -o myorg 2>/dev/null
sf data360 query vector -o myorg --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null
sf data360 query hybrid -o myorg --index Knowledge_Index --query "reset password" --limit 5 2>/dev/null

Example payloads

examples/search-indexes/vector-knowledge.json
examples/search-indexes/hybrid-structured.json

References

SKILL.md
../data360-orchestrate/assets/definitions/search-index.template.json
CREDITS.md

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How it compares

Pick generating-flow over generic Apex guidance when the deliverable must be deployable Flow metadata XML grounded in org object definitions.

FAQ

Which Salesforce Flow types does generating-flow support?

generating-flow supports Screen, Autolaunched, Record-Triggered (before/after-save), and Scheduled flows. It is the only skill in afv-library dedicated to Flow metadata generation.

What MCP steps does generating-flow require?

generating-flow runs fetchGroundedObjectMetadata, then flowElementSelection, then flowElementGeneration before emitting Flow XML through execute_metadata_action.

Is Generating Flow safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

Automation & Workflowsautomationagents

About

Generating Flow by the numbers

Add your badge

How do you generate Salesforce Flow XML metadata?

Who is it for?

When should I use this skill?

What you get

By the numbers

Files

data360-query: Data Cloud Retrieve Phase

When This Skill Owns the Task

Required Context to Gather First

Core Operating Rules

Recommended Workflow

1. Classify readiness for retrieve work

2. Choose the smallest correct query shape

3. Use describe before guessing fields

4. Use vector or hybrid search only when an index exists

5. Reuse curated search-index examples when creating indexes

High-Signal Gotchas

Output Format

References

Credits & Acknowledgments

data360-query

Use this skill for

Example requests

Common commands

Example payloads

References

Related skills

How it compares

FAQ

Which Salesforce Flow types does generating-flow support?

What MCP steps does generating-flow require?

Is Generating Flow safe to install?

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