wdm0006/capturing-contacts-in-evergreen
skills/contact-capture/SKILL.md
Parses unstructured text (email signatures, business cards, LinkedIn profiles, meeting notes) into structured Evergreen CRM contacts. Use when adding new contacts from raw text, importing contacts from emails or messages, or batch-creating contacts from event notes.
data-ai
Updated Apr 23, 2026
$ install --global
skillsauthnpx skillsauth add wdm0006/evergreen-skills capturing-contacts-in-evergreenInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 24, 2026, 2:31 AM178.8s1 file scanned
SKILL.md
- name:
- capturing-contacts-in-evergreen
- description:
- Parses unstructured text (email signatures, business cards, LinkedIn profiles, meeting notes) into structured Evergreen CRM contacts. Use when adding new contacts from raw text, importing contacts from emails or messages, or batch-creating contacts from event notes.
Smart Contact Capture
Works with Evergreen, a local-first personal CRM for macOS. Get it on the Mac App Store.
When to Use
- Someone shares a business card or email signature
- You have raw text with contact details (from a conference, email thread, or LinkedIn)
- You need to batch-create contacts from meeting notes or an event attendee list
- You received an introduction email and want to add the new person
How It Works
- Parse the unstructured text to extract: name, title, organization, email, phone, location, and any contextual notes
- Search existing contacts with
search_contactsto check for duplicates - If the contact doesn't exist, create it with
contacts.create - Add relevant tags with
tags.add_to_contact(e.g., "met-at-conference", "investor", "lead") - Append context notes with
notes.append(how you met, who introduced you, conversation topics) - If an introduction, log the interaction with
interactions.log
Extraction Patterns
| Source | What to Extract | |--------|----------------| | Email signature | Name, title, org, email, phone, address | | LinkedIn URL | Name, headline as title, company as org | | Business card text | All fields, watch for multiple phone/email | | Meeting notes | Names, affiliations, discussion context | | Introduction email | Both parties, relationship context, reason for intro |
Example
Input:
Hey, great meeting Sarah Chen at the AI dinner last night. She's the
CTO at Meridian Health, based in Atlanta. Her email is [email protected]
and she's really interested in our API work.
Actions:
1. search_contacts("Sarah Chen") → no match
2. contacts.create({
first_name: "Sarah",
last_name: "Chen",
title: "CTO",
organization: "Meridian Health",
email: "[email protected]",
location: "Atlanta"
})
3. tags.add_to_contact(contact_id, ["ai", "healthcare", "atlanta"])
4. notes.append(contact_id, "Met at Atlanta AI Dinner. Interested in our API work.")
5. interactions.log(contact_id, type: "meeting", summary: "Met at Atlanta AI Dinner — discussed API work")
Checklist
Contact Capture:
- [ ] Name parsed correctly (first/last split)
- [ ] Duplicate check performed before creating
- [ ] All available fields populated
- [ ] Tags applied for context/source
- [ ] Meeting context saved in notes
- [ ] Initial interaction logged
Learn More
- Evergreen — Local-First Personal CRM
- Vibe Coding a Personal CRM
- Evergreen Gets Serious
- Evergreen Gets Even Evergreener
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