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Based on SOC occupation classification
Showing SKILL.md
| name | log-activity |
| description | Log activity to activities.csv |
Logging outreach activities (calls, messages, emails)
| What | Path |
|---|---|
| Activities | $CRM_PATH/activities.csv |
| People | $CRM_PATH/contacts/people.csv |
activity_id,linkedin_url,date,channel,activity_type,message_preview,result,response_quality,next_followup_date,audience_segment,hook_type,notes
import pandas as pd
from datetime import date, timedelta
import uuid
activities = pd.read_csv('$CRM_PATH/activities.csv')
new_activity = {
'activity_id': f'act-{uuid.uuid4().hex[:8]}',
'linkedin_url': 'https://linkedin.com/in/example', # or email
'date': str(date.today()),
'channel': 'telegram', # linkedin/email/twitter/telegram/whatsapp
'activity_type': 'dm', # dm/connect_request/followup/email/call/research
'message_preview': 'Hi! This is Ivan from WeLabelData...', # first 100 characters
'result': 'sent', # sent/replied/no_response/accepted/rejected
'response_quality': '', # positive/neutral/negative/meeting
'next_followup_date': str(date.today() + timedelta(days=7)),
'audience_segment': 'training_course',
'hook_type': 'course_invitation',
'notes': ''
}
activities = pd.concat([activities, pd.DataFrame([new_activity])], ignore_index=True)
activities.to_csv('$CRM_PATH/activities.csv', index=False)
people = pd.read_csv('$CRM_PATH/contacts/people.csv')
mask = people['linkedin_url'] == 'https://linkedin.com/in/example'
people.loc[mask, 'status'] = 'contacted'
people.loc[mask, 'last_contact_date'] = str(date.today())
people.loc[mask, 'next_followup_date'] = str(date.today() + timedelta(days=7))
people.loc[mask, 'last_updated'] = str(date.today())
people.to_csv('$CRM_PATH/contacts/people.csv', index=False)
linkedin -- LinkedIn DMemail -- Emailtelegram -- Telegramwhatsapp -- WhatsApptwitter -- Twitter/Xdm -- Direct messageconnect_request -- Connection requestfollowup -- Follow-up contactemail -- Email messagecall -- Phone callresearch -- Research (not outreach)sent -- Sent, waiting for responsereplied -- Received a responseno_response -- No response (after N days)accepted -- Accepted request/invitationrejected -- Declinedpositive -- Interestedneutral -- Neither yes nor nonegative -- Not interestedmeeting -- Meeting scheduledFor mass outreach -- log multiple at once:
sent_to = ['email1@test.com', 'email2@test.com', 'email3@test.com']
for email in sent_to:
new_activity = {
'activity_id': f'act-{uuid.uuid4().hex[:8]}',
'linkedin_url': email, # using email as ID
'date': str(date.today()),
'channel': 'telegram',
'activity_type': 'dm',
'result': 'sent',
# ...
}
activities = pd.concat([activities, pd.DataFrame([new_activity])], ignore_index=True)
telegram-send -- before loggingupdate-lead -- update person status