HubSpot CRM Database Audit#

Run a full diagnostic audit of a HubSpot CRM portal. This skill collects metrics across eight dimensions, grades each one, and produces a prioritized report with actionable recommendations.

Setup#

1. Get the API token. Check .env for HUBSPOT_API_TOKEN. If it is not set, ask the user to provide their HubSpot private app API token and store it in .env: text

   HUBSPOT_API_TOKEN=pat-na1-xxxxxxxx
   
   

2. Install dependencies. Use uv (not pip): bash

   uv pip install hubspot-api-client python-dotenv
   
   

3. Create the output directory if it does not exist: bash

   mkdir -p reports
   
   

Audit Dimensions#

Run queries for each of the following eight dimensions. Collect exact counts for every metric listed.

1. Database Size#

• Total contacts
• Total companies
• Total deals
• Marketing contacts vs non-marketing contacts (if Marketing Hub is active)

2. Email Deliverability#

• Hard bounced contacts ( hs_email_hard_bounce_reason_enum is not empty)
• Soft bounced contacts ( hs_email_bounce > 0 AND no hard bounce)
• Global unsubscribes ( hs_is_unworked or hs_email_optout = true)
• Never-emailed contacts (no hs_email_last_send_date)
• Invalid email format (regex check on email property)
• Contacts with 3+ bounces

3. Data Completeness#

• Missing email
• Missing company (contact-level)
• Missing industry (contact-level)
• Missing country and/or state
• Missing lifecyclestage
• Missing hubspot_owner_id
• Missing jobtitle
• Companies missing domain
• Companies missing industry
• Companies missing city / state / country

4. Engagement Health#

• Last activity distribution: active in last 30 days, 31-90 days, 91-180 days, 181-365 days, 365+ days, never engaged
• Email open rate (last 90 days)
• Email click rate (last 90 days)
• Contacts with zero page views
• Contacts with zero form submissions

5. Duplicate Analysis#

• Duplicate email addresses (exact match)
• Companies sharing the same domain
• Companies with very similar names (fuzzy — note: API cannot do fuzzy matching natively; count exact duplicates on name and flag for manual review)

6. Owner Health#

• Deactivated owners who still have assigned contacts
• Deactivated owners who still have assigned companies
• Deactivated owners who still have assigned deals
• Contacts with no owner
• Companies with no owner

7. List & Workflow Health#

• Total active lists vs static lists
• Lists with zero members
• Workflows currently active
• Workflows that have not enrolled anyone in 90+ days
• Forms with zero submissions
• Forms with submissions in last 30 days

8. Deal Pipeline Health#

• Deals without amount
• Deals without closedate
• Deals in each pipeline stage
• Stale deals (no activity in 60+ days, still open)
• Average deal age by stage

API Technical Notes#

These details are critical for getting accurate results:

• Null checks: Use the NOT_HAS_PROPERTY filter operator to find contacts where a property has never been set. HubSpot stores "never happened" as null (property absent), not as 0 or empty string. python

  {
      "filterGroups": [{
          "filters": [{
              "propertyName": "hs_email_last_send_date",
              "operator": "NOT_HAS_PROPERTY"
          }]
      }]
  }
  
  

• Search API pagination limit: The Search API returns a maximum of 10,000 results per query. If you expect more than 10K, segment queries by another property (e.g., createdate ranges, lifecycle stage, or first letter of email) and sum the results.

• Deactivated owners: The Owners API does not return deactivated owners by default. Pass archived=True: python

  api_client.crm.owners.owners_api.get_page(archived=True)
  
  

• Rate limiting: Private apps are limited to 100 requests per 10 seconds. Add a small delay between batch calls or use exponential backoff on 429 responses.

• Engagement timestamps: Use hs_last_sales_activity_timestamp and notes_last_contacted for activity dating. hs_email_last_open_date and hs_email_last_click_date are useful for email engagement specifically.

• Marketing contact status: The property hs_marketable_status indicates whether a contact is set as a marketing contact. This property is read-only via API.

Script Structure#

Write a single Python script ( scripts/audit_portal.py) that:

1. Loads the API token from .env

2. Initializes the HubSpot client: python

   from hubspot import HubSpot
   api_client = HubSpot(access_token=os.getenv("HUBSPOT_API_TOKEN"))
   
   

3. Runs each dimension's queries sequentially (respect rate limits)

4. Collects all results into a structured dict

5. Computes letter grades per dimension (see grading rubric below)

6. Renders the markdown report

7. Saves to reports/hubspot-audit-{YYYY-MM-DD}.md

Grading Rubric#

Assign a letter grade to each dimension based on severity:

GradeMeaningCriteriaAHealthy< 5% of records affectedBMinor issues5-15% of records affectedCNeeds attention15-30% of records affectedDSignificant problems30-50% of records affectedFCritical> 50% of records affected

For dimensions without a simple percentage (e.g., Owner Health), use judgment based on the number of affected records and business impact.

Output Format#

Save the report to reports/hubspot-audit-{YYYY-MM-DD}.md with this structure:

markdown

# HubSpot CRM Audit Report

**Date:** YYYY-MM-DD
**Portal ID:** [portal-id]

## Executive Summary

| Dimension | Grade | Key Finding |
|-----------|-------|-------------|
| Database Size | B | ~XX,000 contacts, XX,000 companies |
| Email Deliverability | D | XX% hard bounced, XX% globally unsubscribed |
| Data Completeness | F | XX% missing email, XX% missing industry |
| Engagement Health | D | XX% never engaged, XX% inactive 12+ months |
| Duplicate Analysis | C | ~X,XXX duplicate company domains |
| Owner Health | F | X deactivated owners with XX,XXX assigned contacts |
| List & Workflow Health | B | XX unused lists, X stale workflows |
| Deal Pipeline Health | C | XX% deals missing amount, XX stale deals |

**Overall Grade: X**

## Priority Recommendations

1. **[CRITICAL] Delete contacts with no email** — XX,XXX contacts with no email address
   are unbillable dead weight. Run `/delete-no-email-contacts`.
   *Effort: 1 hour | Fully scriptable*

2. **[CRITICAL] Suppress hard bounced contacts** — XX,XXX hard bounces are destroying
   sender reputation. Run `/suppress-hard-bounced`.
   *Effort: 1 hour | Hybrid (API + workflow)*

3. **[HIGH] Reassign deactivated owner contacts** — XX,XXX contacts assigned to
   X deactivated users. Run `/reassign-deactivated-owners`.
   *Effort: 2 hours | Fully scriptable*

4. ...continue ranked by impact...

---

## Detailed Findings

### 1. Database Size

| Metric | Count | % of Total |
|--------|-------|------------|
| Total Contacts | XX,XXX | — |
| Total Companies | XX,XXX | — |
| Total Deals | X,XXX | — |
| Marketing Contacts | XX,XXX | XX% |

### 2. Email Deliverability

| Metric | Count | % of Contacts |
|--------|-------|---------------|
| Hard Bounced | X,XXX | XX% |
| Soft Bounced | X,XXX | XX% |
| Global Unsubscribes | X,XXX | XX% |
| Never Emailed | XX,XXX | XX% |
| Invalid Email Format | XXX | X% |

...continue for all 8 dimensions...

---

## Next Steps

Run `/hubspot-implementation-plan` to generate a phased cleanup plan based on these findings.

Skill Prescription#

After generating the audit report, prescribe a specific ordered list of skills the user should run. Do not just present findings — tell the user exactly what to do next.

Step 1: Map Findings to Skills#

For each audit finding that scored C or worse, map it to the appropriate skill. Use this category-ordered lookup:

Database Hygiene (run first — billing and deliverability impact):

FindingSkillPriorityContacts missing email/delete-no-email-contactsP0Hard bounced contacts/suppress-hard-bouncedP0Global unsubscribes/suppress-global-unsubscribesP0Ghost/never-engaged contacts/suppress-ghost-contactsP1Duplicate companies/merge-duplicate-companiesP1Deactivated owners with contacts/reassign-deactivated-ownersP1

Data Enrichment (run second — data quality):

FindingSkillPriorityMissing company name/enrich-company-nameP1Missing industry/enrich-industryP1Inconsistent geo data/standardize-geo-valuesP2Missing geo data/backfill-geo-dataP2Missing/wrong lifecycle stage/fix-lifecycle-stagesP1Unowned marketing contacts/assign-unowned-contactsP1

Segmentation & Scoring (run third — targeting):

FindingSkillPriorityNo ICP classification/create-icp-tiersP2No lead scoring/build-lead-scoringP2No segment lists/build-smart-listsP2

Automation Workflows (run fourth — prevention):

FindingSkillPriorityNo new-contact hygiene/new-contact-hygiene-workflowP2High disengagement rate/engagement-suppression-workflowP2No lifecycle automation/lifecycle-progression-workflowP3No bounce monitoring/bounce-monitoring-workflowP2

Ongoing Maintenance (run last — sustainability):

FindingSkillPriorityUnused lists/cleanup-listsP3Unused forms/cleanup-formsP3Stale workflows/cleanup-workflowsP3Dashboard clutter/cleanup-dashboardsP3Deal pipeline issues/cleanup-dealsP3Unused properties/cleanup-propertiesP3

Step 2: Present the Ordered Prescription#

After the audit report, present a numbered action list — not just findings. Format like this:

markdown

## Your Cleanup Prescription

Based on the audit, here are the skills you should run, in order:

### Immediate (this week)
1. `/delete-no-email-contacts` — X,XXX contacts with no email are inflating your bill
2. `/suppress-hard-bounced` — X,XXX hard bounces are hurting deliverability
3. `/suppress-global-unsubscribes` — X,XXX unsubscribes still counting as marketing contacts

### Next (weeks 2-3)
4. `/reassign-deactivated-owners` — X deactivated users still own X,XXX contacts
5. `/enrich-company-name` — XX% of contacts missing company name
6. `/fix-lifecycle-stages` — X,XXX contacts in invalid lifecycle stages
...

### Later (weeks 4-6)
7. `/create-icp-tiers` — No ICP classification exists yet
8. `/build-lead-scoring` — No scoring model in place
...

Step 3: Handle Missing Skills#

If the audit reveals a problem that no existing skill covers, do the following:

1. Tell the user clearly: "This audit found an issue that isn't covered by any existing skill: [description]."

2. Offer to create it on the spot: "I can create a new skill for this right now. It would be called /[suggested-name] and would handle [brief description]."

3. Ask about contributing upstream: "Would you like to contribute this new skill back to the community? If yes, I'll:

   • Create the skill in skills/[name]/SKILL.md
   • Fork the repo (if not already forked)
   • Push the new skill to your fork
   • Open a pull request to tomgranot/hubspot-admin-skills

This helps everyone who uses these skills in the future."

1. If the user agrees, create the skill following the standard SKILL.md format, commit it, and open the PR.

2. If the user declines the upstream contribution, still create the skill locally so they can use it.

Step 4: Suggest Next Step#

End with:

text

Ready to start? Run `/hubspot-implementation-plan` to generate a full phased plan,
or jump straight to the first skill: `/delete-no-email-contacts`.

After Running#

• Print the file path of the saved report
• Present the ordered skill prescription (Step 2 above)
• Highlight the top 3 most critical findings
• Flag any findings that have no matching skill (Step 3 above)
• Suggest running /hubspot-implementation-plan for the full phased plan