Platform Destructive Deploy logo

Platform Destructive Deploy

OrganizationPopular
forcedotcom
platform-destructive-deploy

Execute the destructiveChanges.xml delete-and-deploy workflow against a Salesforce org. TRIGGER when the user asks to delete/remove a custom object, field, Apex class, flow, or any metadata component FROM an org, or to perform a 'destructive deploy' / removal as part of a release. Validates first and gates production with explicit confirmation. DO NOT TRIGGER for local file deletion (use Bash), or for net-new deploys (use platform-metadata-deploy).

Overview

Publisherforcedotcom
Repositorysf-skills
Skill nameplatform-destructive-deploy
Stars
1.1K
Forks
351
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by forcedotcom on GitHub. Read the source before you install it.

Installation

Install the Platform Destructive Deploy AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/forcedotcom/sf-skills/tree/main/plugins/builder/salesforce-development/skills/platform-destructive-deploy
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/forcedotcom/sf-skills.git /tmp/sf-skills
mkdir -p .claude/skills
cp -r /tmp/sf-skills/plugins/builder/salesforce-development/skills/platform-destructive-deploy .claude/skills/platform-destructive-deploy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Platform Destructive Deploy in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Platform Destructive Deploy on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Platform Destructive Deploy is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Handling Destructive Changes

Coordinate metadata deletion against a Salesforce org via the destructiveChanges manifest. Runs in three phases: scope → validate → execute, with stricter guardrails for production.

Phase 1 — Scope the deletion

Step 1a — Gather the components to remove

Ask the user (or infer from context) which components to delete. For each, capture:

  • Metadata type (e.g. CustomObject, CustomField, ApexClass, Flow, PermissionSet)
  • API name (e.g. Project__c, Account.Status__c, MyController)

Step 1b — Local dependency scan (best-effort)

Before generating the manifest, scan the local project for references to each component. Use Grep over force-app/:

bash
grep -rn "<componentApiName>" force-app/ --include='*.cls' --include='*.trigger' --include='*.xml' --include='*.js' --include='*.html'

If references are found:

  • List them to the user
  • Recommend either updating those references first OR removing them in the same destructive deploy
  • Do NOT proceed silently — surface the dependency risk

Step 1c — Generate destructiveChanges.xml

Write to manifest/destructiveChangesPre.xml (for pre-deploy deletion) or manifest/destructiveChangesPost.xml (for post-deploy deletion). Use the standard Salesforce metadata format:

xml
<?xml version="1.0" encoding="UTF-8"?>
<Package xmlns="http://soap.sforce.com/2006/04/metadata">
    <types>
        <members>Project__c</members>
        <members>OldThing__c</members>
        <name>CustomObject</name>
    </types>
    <types>
        <members>Account.Status__c</members>
        <name>CustomField</name>
    </types>
    <version>62.0</version>
</Package>

Use the API version from sfdx-project.json's sourceApiVersion.

Group components by metadata type (one <types> block per type). For namespaced fields, use Object.Field notation.

Phase 2 — Validate

ALWAYS validate before executing a destructive deploy:

bash
sf project deploy validate \
  --pre-destructive-changes manifest/destructiveChangesPre.xml \
  --manifest manifest/package.xml \
  --target-org <alias> \
  --test-level RunLocalTests \
  --json

(For post-destructive: use --post-destructive-changes.)

If package.xml doesn't exist, create an empty one alongside (deletion-only deploy needs a package descriptor):

xml
<?xml version="1.0" encoding="UTF-8"?>
<Package xmlns="http://soap.sforce.com/2006/04/metadata">
    <version>62.0</version>
</Package>

If validation fails, surface errors and STOP. Common failure modes:

  • "Cannot delete: referenced by Apex/Flow/Layout" → component still has references
  • "Cannot delete: required for license" → managed-package or license dependency
  • "Insufficient access" → user lacks delete permission

Phase 3 — Execute

Production path

Confirm whether the target is production before executing. The reliable check is the gate's classifier (returns production|sandbox|scratch|trial|devhub|unknown):

bash
sf org display --target-org <alias> --json | "${CLAUDE_PLUGIN_ROOT}/scripts/sf-deploy-gate" classify

If the classifier returns production:

  1. Display destructive confirmation banner (mirroring platform-quick-deploy)
  2. List EVERY component that will be deleted
  3. Require explicit "yes, delete from PRODUCTION" confirmation
  4. Reject --purge-on-delete unless the user types it explicitly

The PreToolUse hook (sf-deploy-gate destructive) will already block bare destructive commands against prod — surface that denial to the user, do not work around it.

Sandbox / Scratch path

bash
sf project deploy start \
  --pre-destructive-changes manifest/destructiveChangesPre.xml \
  --manifest manifest/package.xml \
  --target-org <alias> \
  --json \
  --wait 30

Add --purge-on-delete only if the user explicitly asked to permanently delete (skip the recycle bin).

Phase 4 — Post-delete cleanup

After a successful destructive deploy:

  • Recommend a sf project retrieve start --metadata <Type>:<Name> is NOT useful (component is gone) — instead suggest cleaning up the local source:
    bash
    # Remove the now-deleted local files to keep source tracking accurate
    rm -rf force-app/main/default/<path-to-component>
  • If deleting a custom field with data, remind the user that data is gone (or in the recycle bin until purged)
  • Recommend running tests to confirm no runtime regressions

Rules

  • ALWAYS validate first; NEVER skip Phase 2
  • ALWAYS scan for local references; NEVER delete blindly
  • ALWAYS gate production with explicit user confirmation
  • NEVER add --purge-on-delete without explicit user request
  • NEVER use --ignore-errors on a destructive deploy
  • ALWAYS use the API version from sfdx-project.json, not a hardcoded value
  • If the user is deleting a field with required="true" or that's used in RecordType picklist values, surface the cascade impact before proceeding

Frequently asked questions

What does the Platform Destructive Deploy AI skill do?

Execute the destructiveChanges.xml delete-and-deploy workflow against a Salesforce org. TRIGGER when the user asks to delete/remove a custom object, field, Apex class, flow, or any metadata component FROM an org, or to perform a 'destructive deploy' / removal as part of a release. Validates first and gates production with explicit confirmation. DO NOT TRIGGER for local file deletion (use Bash), or for net-new deploys (use platform-metadata-deploy).

Why use Platform Destructive Deploy on TypingMind?

Because you install it once and use it with any model. Platform Destructive Deploy is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Platform Destructive Deploy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/forcedotcom/sf-skills/tree/main/plugins/builder/salesforce-development/skills/platform-destructive-deploy. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Platform Destructive Deploy?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Platform Destructive Deploy?

As many as you like. As long as a model supports skills, you can use Platform Destructive Deploy with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Platform Destructive Deploy AI skill free?

Yes. It is published on GitHub by forcedotcom under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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