Slack Lead Scanner

Monitor #leadscanner for new images/text, process as leads via Apollo + HubSpot, reply in-thread. Also check Slack DM replies to update HubSpot contacts.

Setup

• - SLACK_TOKEN in ~/.openclaw/credentials/slack-bot-token (xoxb- token)
• Apollo key in ~/.openclaw/credentials/apollo-api-key
• HubSpot token in ~/.openclaw/credentials/hubspot-api-key
• State file: ~/clawd/memory/slack-lead-scanner-state.json
• Portal ID: 43856876
• Channel: #leadscanner (C0AQAJ8VD8A)

State File Schema

CODEBLOCK0

Polling Workflow

Part 1: Process New #leadscanner Messages

1. 1. Load state from ~/clawd/memory/slack-lead-scanner-state.json
2. Fetch messages: INLINECODE0
3. Filter: ts > lastts, not in processedids, has files or non-empty text
4. For each new message:

a. Download image: curl -H "Authorization: Bearer $SLACK_TOKEN" "[file.url_private_download]" -o /tmp/lead-[ts].jpg b. Analyze with image tool: "Extract structured data from this badge or business card. Return JSON: {firstname, lastname, company, title, email, phone, notes}" c. Append message.text to notes d. Dedup: Search HubSpot first by firstname+lastname+company — if exists, skip enrich, go to step (g) e. Enrich via Apollo: curl -X POST -H "Content-Type: application/json" -d '{"api_key":"[KEY]","first_name":"[f]","last_name":"[l]","organization_name":"[co]","title":"[t]","reveal_personal_emails":true,"reveal_phone_number":true}' https://api.apollo.io/api/v1/people/match f. Sleep 10s, then search HubSpot for new contact (sort by createdate DESC, filter name+company) g. Get contact id, build link: https://app.hubspot.com/contacts/43856876/contact/[id] h. Send DM to Mark (user:U03H7C6HW5B) with formatted message (see Reply Format below) i. Track DM timestamp from response, add to pendingdmreplies in state j. React ✅ on original #leadscanner message k. Add msg ts to processedids, update lastts l. Cleanup: INLINECODE4

Part 2: Check DM Replies for HubSpot Updates

1. 5. For each entry in pendingdmreplies:

a. Fetch thread replies: curl -H "Authorization: Bearer $SLACK_TOKEN" "https://slack.com/api/conversations.replies?channel=[DM_CHANNEL_ID]&ts=[dm_ts]" b. Filter replies that are from the user (not the bot itself) and not yet processed c. Parse reply text as a natural-language HubSpot update instruction, e.g.: - "update title to VP of Sales" → jobtitle - "wrong email, it's john@acme.com" → email - "company is Acme Corp" → company - "phone is 415-555-1234" → phone - "add note: met at SaaStr" → note (create HubSpot note via /crm/v3/objects/notes) d. Apply update via HubSpot PATCH: curl -X PATCH -H "Authorization: Bearer $HUBSPOT_TOKEN" -H "Content-Type: application/json" -d '{"properties":{"[field]":"[value]"}}' "https://api.hubapi.com/crm/v3/objects/contacts/[hubspot_contact_id]" e. Reply in thread: "✅ Updated [field] to [value] for [contact_name]." f. If unrecognized instruction, reply: "❓ I didn't understand that. Try: 'update title to [value]' or 'email is [value]'"

1. 6. Write updated state back to ~/clawd/memory/slack-lead-scanner-state.json
2. Log to memory/YYYY-MM-DD.md

Reply Format (DM to Mark)

Use Slack line breaks (\n) between fields:

CODEBLOCK1

HubSpot Field Mappings

Natural language	HubSpot property
name / first name / last name	firstname / lastname
title / job title / role

jobtitle | | company / org | company | | email | email | | phone | phone | | note / notes | create note object |

Error Handling

• - No Apollo match: send DM anyway with extracted data, note "No enrichment match"
• No HubSpot match after sleep: send DM with "Sync pending - check HubSpot later", omit link
• API errors: Log and DM "Error processing: [msg]" with ❌ react
• Unknown DM reply: Reply with ❓ and guidance

Notes

• - Use haiku model for cost efficiency
• Rate limits: Slack ~1 call/sec, Apollo per plan, HubSpot 100 req/10s
• Never log or output tokens
• Get DM channel ID for direct messages: it's a conversations.open response for user U03H7C6HW5B