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Sf Deploy

  • 33 installs
  • 423 repo stars
  • Updated April 27, 2026
  • jaganpro/claude-code-sfskills

This is a copy of sf-deploy by jaganpro - installs and ranking accrue to the original listing.

Helps with devops & ci/cd tasks.

About

sf-deploy is a Claude Code skill for devops & ci/cd. It helps solo builders move faster with AI-assisted development.

  • sf-deploy
  • DevOps & CI/CD
  • AI-coding skill

Sf Deploy by the numbers

  • 33 all-time installs (skills.sh)
  • Data as of Aug 2, 2026 (Skillselion catalog sync)
npx skills add https://github.com/jaganpro/claude-code-sfskills --skill sf-deploy

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Listed on Skillselion
Installs33
repo stars423
Last updatedApril 27, 2026
Repositoryjaganpro/claude-code-sfskills

What it does

Helps with devops & ci/cd tasks.

Files

SKILL.mdMarkdownGitHub ↗

sf-deploy: 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 sf-deploy 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 or LWC code → sf-apex, sf-lwc
  • creating metadata definitions → sf-metadata
  • building Flows → sf-flow
  • doing org data operations → sf-data
  • authoring Agent Script logic → sf-ai-agentscript

---

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 `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 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) as documented in sf-apex.

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 skills for authoring decisions:

  • sf-ai-agentscript for .agent authoring and validation
  • sf-ai-agentforce for Agent Builder / Prompt Builder / 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 / field creationsf-metadatadefine metadata before deploy
Apex compile / review / fixessf-apexcode authoring and repair
Flow creation / repairsf-flowFlow authoring and activation guidance
test data or seed recordssf-datadescribe-first data setup and cleanup
Agent Script build/publish readinesssf-ai-agentscriptagent-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

---

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>

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