dx-org-analyze

SkillProductivity

Lets your agent compare two Salesforce orgs or inventory one org's metadata, permissions, packages, and limits.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the dx-org-analyze skill

About this capability

Compare two Salesforce orgs side-by-side and produce a comparison report with drift score, or analyze a single org to produce an inventory covering metadata components, org permissions, system permissions, profiles, installed packages, licenses, and org limits. Use this skill when the user wants to

What this skill tells your AI

The instructions your AI receives, as published by forcedotcom/sf-skills in skills/dx-org-analyze/SKILL.md and read by ahel’s review.

Tool Restrictions

Use ONLY the Bash tool to execute all sf CLI commands and Python scripts. Always include --json for sf commands. Do NOT use mcp__salesforce_dx__* tools.

Output artifacts for eval/testing: When an output directory is available, write results there. After executing the skill: (1) if the user specified an output path, write there immediately; (2) otherwise run [ -d force-app/main/adk-eval-output/ ] && echo 'force-app/main/adk-eval-output' to detect the eval directory; (3) write the full JSON result to <output-dir>/dx-org-analyze-result.json and the markdown report to <output-dir>/dx-org-analyze-result.md.


Data Access Hierarchy

When querying org data, always follow this priority order:

  1. SF CLI commands — Preferred. Use sf org list metadata-types, sf org list metadata, sf org display, sf data query, sf limits api display, etc.
  2. Direct REST/Tooling API calls — Last resort, only when SF CLI cannot provide the data.

Never bypass this hierarchy. If an SF CLI command exists for the operation, use it even if a direct API call would be simpler.


Authentication Rules

  • All authentication MUST go through SF CLI (sf org login web, sf org login jwt, sf org login access-token).
  • Never accept raw credentials (username + password), session IDs, or access tokens directly from the user.
  • The collection script obtains its access token exclusively via sf org display --json.

Workflow

Step 0: List Authenticated Orgs

Run this command to discover all authenticated orgs:

sf org list --json --skip-connection-status

Parse the JSON output. Collect orgs from all buckets (devHubs, nonScratchOrgs, scratchOrgs, sandboxes, other). Present authenticated orgs in a readable table:

#AliasUsernameInstance URLOrg IDType

If fewer than 2 orgs are authenticated but at least 1 is available, offer the single-org introspect mode (see Introspect Workflow below). If no orgs are authenticated, STOP and advise:

You need at least 1 authenticated org. Run sf org login web --alias <name> to authenticate.

If the user explicitly requests a single-org introspection or inventory, use the Introspect Workflow regardless of how many orgs are available.

Step 1: User Selects Two Orgs

Ask the user to select two orgs from the list. Both must be explicitly named — do NOT allow implicit/default orgs.

Select two orgs to compare. Which is the source (reference/expected state)? Which is the target (to compare against)?

Accept: alias, username, or number from the list. Resolve each selection to a concrete username. If an org lacks an alias, prompt the user to assign one. Confirm:

Comparing:

  • Source: <alias> (<username>)
  • Target: <alias> (<username>)

Step 2: Validate Connectivity

For each org, confirm reachability with a lightweight query that does not expose secrets:

sf data query --target-org <alias-or-username> --query "SELECT Id FROM Organization LIMIT 1" --json

If the query succeeds (exit 0 and a record is returned), the org is connected. If it fails with INVALID_SESSION_ID or auth errors:

sf org login web --alias <alias>

Step 3: Collect Data (per org)

Generate a unique run ID and run the collection script for each org:

RUN_ID=$(date +%Y%m%d-%H%M%S)

python3 ./scripts/collect_org_data.py \
  --org-alias "$SOURCE_ORG" \
  --output /tmp/dx-org-comparison-${RUN_ID}-source

python3 ./scripts/collect_org_data.py \
  --org-alias "$TARGET_ORG" \
  --output /tmp/dx-org-comparison-${RUN_ID}-target

Exit codes: 0 = success, 1 = fatal error (report stderr to user), 2 = session expired (re-authenticate Step 2 and retry).

For details on what the collection script gathers, see references/collection-details.md.

Step 4: Compute Diff and Report

python3 ./scripts/compute_diff.py \
  --org-a /tmp/dx-org-comparison-${RUN_ID}-source \
  --org-b /tmp/dx-org-comparison-${RUN_ID}-target \
  --output /tmp/dx-org-comparison-${RUN_ID} \
  --format both \
  --org-a-label "Source" \
  --org-b-label "Target"

Use --show-shared if the user wants shared components listed in detail.

Step 5: Present Results

Read /tmp/dx-org-comparison-${RUN_ID}.md and present to the user. If the user asks follow-up questions, use /tmp/dx-org-comparison-${RUN_ID}.json for data lookups. Then resolve the output directory and copy both files there:

OUTPUT_DIR=""
if [ -n "$USER_OUTPUT_PATH" ]; then
  OUTPUT_DIR="$USER_OUTPUT_PATH"
elif [ -d "force-app/main/adk-eval-output" ]; then
  OUTPUT_DIR="force-app/main/adk-eval-output"
fi

if [ -n "$OUTPUT_DIR" ]; then
  cp /tmp/dx-org-comparison-${RUN_ID}.json "$OUTPUT_DIR/dx-org-analyze-result.json"
  cp /tmp/dx-org-comparison-${RUN_ID}.md "$OUTPUT_DIR/dx-org-analyze-result.md"
fi

Introspect Workflow (Single-Org Mode)

Use this workflow when the user wants to inspect a single org's configuration, or when only one org is authenticated.

Introspect Step 1: Validate Connectivity

sf data query --target-org <alias-or-username> --query "SELECT Id FROM Organization LIMIT 1" --json

Introspect Step 2: Collect Data

RUN_ID=$(date +%Y%m%d-%H%M%S)

python3 ./scripts/collect_org_data.py \
  --org-alias "$ORG" \
  --output /tmp/dx-org-analysis-${RUN_ID}

Introspect Step 3: Generate Report

python3 ./scripts/introspect_org.py \
  --org /tmp/dx-org-analysis-${RUN_ID} \
  --output /tmp/dx-org-analysis-${RUN_ID} \
  --format both \
  --label "OrgName"

Introspect Step 4: Present Results

Read /tmp/dx-org-analysis-${RUN_ID}.md and present to the user. The report covers: metadata inventory, org settings, org limits, installed packages, licenses, system permissions, and deep data records. Then resolve the output directory and copy both files there:

OUTPUT_DIR=""
if [ -n "$USER_OUTPUT_PATH" ]; then
  OUTPUT_DIR="$USER_OUTPUT_PATH"
elif [ -d "force-app/main/adk-eval-output" ]; then
  OUTPUT_DIR="force-app/main/adk-eval-output"
fi

if [ -n "$OUTPUT_DIR" ]; then
  cp /tmp/dx-org-analysis-${RUN_ID}.json "$OUTPUT_DIR/dx-org-analyze-result.json"
  cp /tmp/dx-org-analysis-${RUN_ID}.md "$OUTPUT_DIR/dx-org-analyze-result.md"
fi

Report Structure

The generated report includes:

  1. Drift Score — Weighted overall score (60% metadata, 30% permissions, 10% profiles) with severity level (LOW/MODERATE/HIGH/CRITICAL)
  2. Summary Statistics — Counts per metadata type with Identical/Different columns from deep data
  3. Metadata Components by Type — Only-in-Source, only-in-Target, shared per type
  4. Profiles — Shared, source-only, target-only
  5. Installed Packages — Version comparison, only-in-Source, only-in-Target
  6. Package Components — Namespaced components grouped by namespace
  7. Org Permissions — Boolean enabled/disabled diffs by category, plus value diffs
  8. System Permissions — PermissionsXxx fields on PermissionSet, per-set diffs
  9. Org Values & Limits — Grouped by Identity, Storage, API, Feature Limits
  10. Licenses — User, Permission Set, Package license quantity diffs
  11. Deep Data — Content-level diffs for Apex, Flows, Validation Rules, Custom Fields, etc.

Rules / Constraints

ConstraintRationale
Always use --json with sf commandsStructured output for reliable parsing
Resolve orgs to usernames, not aliasesAliases can be ambiguous; usernames are unique
Skip expired and disconnected orgsCannot query metadata from inaccessible orgs
Read-only — never deploy or modifyThis skill compares only, never mutates either org
SF CLI auth onlyAll authentication through SF CLI credential store
Both orgs must be explicitNever compare unnamed or implicit/default orgs

Troubleshooting

IssueResolution
"No org found for <alias>"Org not authenticated — run sf org login web --alias <name>
Fewer than 2 authenticated orgsAuthenticate additional orgs before comparing
"INVALID_SESSION_ID" or auth errorsSession expired — re-run sf org login web --alias <name>
Collection script exits with code 2Session expired — re-authenticate and retry
API limit errors during metadata listingUse --skip-deep-data for a faster pass with less detail
Edition differences (DE vs EE)Many differences are edition-inherent, not configuration drift
Large orgs timeout on deep dataUse --skip-deep-data flag; run full deep data on targeted follow-ups

Cross-Skill Integration

NeedDelegate to
Retrieve specific metadata from an orgplatform-metadata-retrieve
Deploy metadata to an orgplatform-metadata-deploy
Create a scratch org for comparisondx-org-manage
Switch default org after comparisondx-org-switch

Reference File Index

FileWhen to read
references/collection-details.mdFor details on what the collection script gathers and how
references/report-format.mdFor drift score formula and report section details
scripts/collect_org_data.pyData collection script (per org)
scripts/compute_diff.pyDiff computation and report generation script
scripts/introspect_org.pySingle-org introspection report script

Signals

GitHub stars
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Last commit
Sep 2026
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Catalog kind
skill
Gateway key
dx-org-analyze
Source
github.com/forcedotcom/sf-skills