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Deploying Metadata

  • 534 installs
  • 787 repo stars
  • Updated August 5, 2026
  • forcedotcom/afv-library

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

deploying-metadata is a Claude Code skill that orchestrates Salesforce metadata deployments, scratch org management, dry-run validations, and deployment troubleshooting using the sf CLI v2.

About

deploying-metadata is a version 1.1 skill from forcedotcom/afv-library that automates Salesforce DevOps with the sf CLI v2. The skill handles deployment orchestration including dry-run validation via sf project deploy, targeted org deployments, scratch org and sandbox lifecycle management, and CI/CD pipeline setup. It explicitly avoids Apex authoring, LWC generation, and SOQL queries, directing those to sibling afv-library skills. Developers reach for deploying-metadata when metadata pushes fail, scratch orgs need provisioning, or release pipelines require validated sf CLI deployment steps.

  • Orchestrates sf project deploy start, quick, report and retrieval workflows
  • Handles release sequencing across objects, permission sets, Apex and Flows
  • Provides CI/CD gates, test-level selection and deployment reports
  • Troubleshoots deployment failures and dependency ordering
  • Manages scratch orgs, sandboxes and safe rollout sequencing

Deploying Metadata by the numbers

  • 534 all-time installs (skills.sh)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/forcedotcom/afv-library --skill deploying-metadata

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Listed on Skillselion
Installs534
repo stars787
Last updatedAugust 5, 2026
Repositoryforcedotcom/afv-library

How do you deploy Salesforce metadata with sf CLI?

Safely orchestrate Salesforce metadata deployments, manage scratch orgs, run dry-run validations, and troubleshoot deployment failures using the sf CLI.

Who is it for?

Salesforce developers managing metadata releases who need sf CLI v2 deployment orchestration and dry-run validation before production pushes.

Skip if: Developers writing Apex classes, building LWC components, or querying org data who should use sibling afv-library generation skills instead.

When should I use this skill?

User deploys Salesforce metadata, manages scratch orgs or sandboxes, sets up CI/CD pipelines, or troubleshoots sf project deploy errors.

What you get

Validated deployment manifests, scratch org configurations, CI/CD pipeline steps, and resolved sf project deploy error reports.

  • deployment commands
  • CI/CD pipeline configuration
  • scratch org setup scripts

By the numbers

  • Skill version 1.1 in forcedotcom/afv-library
  • Uses Salesforce sf CLI v2 for all deployment orchestration

Files

SKILL.mdMarkdownGitHub ↗

deploying-metadata: Comprehensive Salesforce DevOps Automation

Use this skill when the user needs deployment orchestration: dry-run validation, targeted or manifest-based deploys, CI/CD workflow advice, scratch-org management, failure triage, or safe rollout sequencing for Salesforce metadata.

When This Skill Owns the Task

Use deploying-metadata when the work involves:

  • sf project deploy start, quick, report, or retrieval workflows
  • release sequencing across objects, permission sets, Apex, and Flows
  • CI/CD gates, test-level selection, or deployment reports
  • troubleshooting deployment failures and dependency ordering

Delegate elsewhere when the user is:

  • authoring Apex code → generating-apex
  • authoring LWC components → generating-lwc-components
  • creating custom objects or fields → generating-custom-object, generating-custom-field
  • building Flows → generating-flow
  • doing org data operations → handling-sf-data
  • authoring or testing Agentforce agents → developing-agentforce

---

Critical Operating Rules

  • Use `sf` CLI v2 only.
  • On non-source-tracking orgs, deploy/retrieve commands require an explicit scope such as --source-dir, --metadata, or --manifest.
  • Prefer `--dry-run` first before real deploys.
  • For Flows, deploy safely and activate only after validation.
  • Keep test-data creation guidance delegated to `handling-sf-data` after metadata is validated or deployed.

Default deployment order

PhaseMetadata
1Custom objects / fields
2Permission sets
3Apex
4Flows as Draft
5Flow activation / post-verify

This ordering prevents many dependency and FLS failures.

---

Required Context to Gather First

Ask for or infer:

  • target org alias and environment type
  • deployment scope: source-dir, metadata list, or manifest
  • whether this is validate-only, deploy, quick deploy, retrieve, or CI/CD guidance
  • required test level and rollback expectations
  • whether special metadata types are involved (Flow, permission sets, agents, packages)

Preflight checks:

sf --version
sf org list
sf org display --target-org <alias> --json
test -f sfdx-project.json

---

Recommended Workflow

1. Preflight

Confirm auth, repo shape, package directories, and target scope.

2. Validate first

sf project deploy start --dry-run --source-dir force-app --target-org <alias> --wait 30 --json

Use manifest- or metadata-scoped validation when the change set is targeted.

3. If validation succeeds, offer the next safe workflow

After a successful validation, guide the user to the correct next action: 1. deploy now 2. assign permission sets 3. create test data via handling-sf-data 4. run tests / smoke checks 5. orchestrate multiple post-deploy steps in order

4. Deploy the smallest correct scope

# source-dir deploy
sf project deploy start --source-dir force-app --target-org <alias> --wait 30 --json

# manifest deploy
sf project deploy start --manifest manifest/package.xml --target-org <alias> --test-level RunLocalTests --wait 30 --json

# manifest deploy with Spring '26 relevant-test selection
sf project deploy start --manifest manifest/package.xml --target-org <alias> --test-level RunRelevantTests --wait 30 --json

# quick deploy after successful validation
sf project deploy quick --job-id <validation-job-id> --target-org <alias> --json

5. Verify

sf project deploy report --job-id <job-id> --target-org <alias> --json

Then verify tests, Flow state, permission assignments, and smoke-test behavior.

6. Report clearly

Summarize what deployed, what failed, what was skipped, and what the next safe action is.

Output template: references/deployment-report-template.md

---

High-Signal Failure Patterns

Error / symptomLikely causeDefault fix direction
FIELD_CUSTOM_VALIDATION_EXCEPTIONvalidation rule or bad test dataadjust data or rule timing
INVALID_CROSS_REFERENCE_KEYmissing dependencyinclude referenced metadata first
CANNOT_INSERT_UPDATE_ACTIVATE_ENTITYtrigger / Flow / validation side effectinspect automation stack and failing logic
tests fail during deploybroken code or fragile testsrun targeted tests, fix root cause, revalidate
field/object not found in permsetwrong orderdeploy objects/fields before permission sets
Flow invalid / version conflictdependency or activation problemdeploy as Draft, verify, then activate

Full workflows: references/orchestration.md, references/trigger-deployment-safety.md

---

CI/CD Guidance

Default pipeline shape: 1. authenticate 2. validate repo / org state 3. static analysis 4. dry-run deploy 5. tests + coverage gates 6. deploy 7. verify + notify

  • When org policy and release risk allow it, consider --test-level RunRelevantTests for Apex-heavy deployments.
  • Pair this with modern Apex test annotations such as @IsTest(testFor=...) and @IsTest(isCritical=true) — see generating-apex for authoring guidance.

Static analysis now uses Code Analyzer v5 (sf code-analyzer), not retired sf scanner.

Deep reference: references/deployment-workflows.md

---

Agentforce Deployment Note

Use this skill to orchestrate deployment/publish sequencing around agents, but use the agent-specific skill for authoring decisions:

  • developing-agentforce for .agent authoring, Agent Builder, Prompt Builder, and metadata config

For full agent DevOps details, including Agent: pseudo metadata, publish/activate, and sync-between-orgs, see:

  • references/agent-deployment-guide.md

---

Cross-Skill Integration

NeedDelegate toReason
custom object creationgenerating-custom-objectdefine objects before deploy
custom field creationgenerating-custom-fielddefine fields before deploy
Apex authoring / fixesgenerating-apexcode authoring and repair
Flow creation / repairgenerating-flowFlow authoring and activation guidance
test data or seed recordshandling-sf-datadescribe-first data setup and cleanup
Agent authoring and publish readinessdeveloping-agentforceagent-specific correctness

---

Reference Map

Start here

  • references/orchestration.md
  • references/deployment-workflows.md
  • references/deployment-report-template.md

Specialized deployment safety

  • references/trigger-deployment-safety.md
  • references/agent-deployment-guide.md
  • references/deploy.sh

Asset templates

  • assets/package.xml — manifest template covering common metadata types
  • assets/destructiveChanges.xml — template for removing metadata from target orgs

---

Score Guide

ScoreMeaning
90+strong deployment plan and execution guidance
75–89good deploy guidance with minor review items
60–74partial coverage of deployment risk
< 60insufficient confidence; tighten plan before rollout

---

Completion Format

Deployment goal: <validate / deploy / retrieve / pipeline>
Target org: <alias>
Scope: <source-dir / metadata / manifest>
Result: <passed / failed / partial>
Key findings: <errors, ordering, tests, skipped items>
Next step: <safe follow-up action>

Related skills

How it compares

Pick deploying-metadata over Apex or LWC generation skills when the task is pushing, validating, or debugging metadata deployments rather than authoring source code.

FAQ

What CLI does deploying-metadata use?

deploying-metadata uses Salesforce sf CLI v2 for metadata deployment orchestration. The skill runs dry-run validations with sf project deploy, manages scratch orgs and sandboxes, and troubleshoots deployment failures.

When should deploying-metadata not be triggered?

deploying-metadata should not be used for writing Apex code, building LWC components, creating custom object metadata, or querying org data. The afv-library provides separate skills for generating-apex, generating-lwc-components, and handling-sf-data.

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