How do I install the Evergreen Relationship Health skill?

Run npx skillmds@latest add wdm0006/evergreen-relationship-health in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Evergreen Relationship Health safe to use?

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Which AI agents work with Evergreen Relationship Health?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Evergreen Relationship Health free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Evergreen Relationship Health?

wdm0006 (@wdm0006) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Evergreen Relationship Health by wdm0006

Name: Evergreen Relationship Health
Author: wdm0006

Evergreen Relationship Health

Scores and surfaces relationship health across your Evergreen CRM contacts — identifies thriving relationships, ones at risk, and dormant connections needing attention. Use when you want a high-level view of your network health or need to prioritize relationship investment.

wdm0006 Updated Sep 17, 2026

File contents

Relationship Health Check

Works with Evergreen, a local-first personal CRM for macOS. Get it on the Mac App Store.

When to Use

Monthly network review: "How healthy is my network?"
When deciding where to invest relationship energy
Before planning outreach for the week
When feeling like you're losing touch with your network

How It Works

Call get_relationship_strength_statistics for the network summary, including the average score and contact count by grade
Call get_relationship_strengths with the Weak grade filter and limit: 100, then repeat with the Dormant grade filter, to build the ranked needs-attention list without scanning every contact
For the handful of contacts included in the report, use get_contact and get_contact_interactions to explain why the relationship needs attention and suggest a specific action
Analyze the global network with get_global_network for cluster and relationship patterns
For a single-contact health check, call get_relationship_strength and supplement it with contact details and interactions as needed

Health Scoring

Evergreen calculates relationship strength scores from 0–100 based on recency, frequency, depth, and variety of interactions. Use the score returned by the relationship-strength tools rather than calculating or weighting these factors in the skill.

Health Grades

Grade	Score	Action
Strong	80–100	Maintain current pace
Good	60–79	No action needed
Moderate	40–59	Consider a check-in
Weak	20–39	Prioritize outreach this week
Dormant	0–19	Re-engagement needed

Example Output

## Network Health Report — April 2026

### Summary
- **Total active contacts:** 127
- **Strong:** 12 (9%)
- **Good:** 34 (27%)
- **Moderate:** 28 (22%)
- **Weak:** 18 (14%)
- **Dormant:** 35 (28%)

### Needs Attention (Top 5 Weak or Dormant)
1. **Marcus Webb** (Founder, DataFlow) — Weak, score 38.
   Was very active (4 interactions in Q1). Partnership proposal pending.
2. **Lisa Park** (VP Product, Meridian) — Weak, score 35. Procurement
   discussion stalled. You owe security questionnaire.
3. **David Kim** (DataTech) — Weak, score 32. Key introducer in your network
   (introduced 4 contacts). Worth maintaining.
4. **Rachel Torres** (Angel investor) — Dormant, score 18. Offered to help with
   hiring, never followed up.
5. **Tom Bradley** (Advisor) — Dormant, score 15. Quarterly coffee overdue.

### Network Insights
- Your most active cluster: Atlanta AI community (23 contacts, avg 18 days between interactions)
- Weakest cluster: College network (15 contacts, avg 140 days between interactions)
- Top introducer going dormant: David Kim — maintain this relationship
- You have 8 contacts with pending actions older than 2 weeks

Checklist

Relationship Health:
- [ ] Relationship strength statistics summarized
- [ ] Strong, Good, Moderate, Weak, and Dormant grades reported
- [ ] Weak and Dormant relationships prioritized by value
- [ ] Specific action suggested for each Weak or Dormant contact
- [ ] Network-level insights provided (clusters, trends)
- [ ] Pending stale actions flagged

Learn More

---name: evergreen-relationship-healthdescription: Scores and surfaces relationship health across your Evergreen CRM contacts — identifies thriving relationships, ones at risk, and dormant connections needing attention. Use when you want a high-level view of your network health or need to prioritize relationship investment.---# Relationship Health Check> Works with [Evergreen](https://heltonlabs.com/evergreen), a local-first personal CRM for macOS. [Get it on the Mac App Store](https://apps.apple.com/us/app/evergreencrm/id6753191506?mt=12).## When to Use- Monthly network review: "How healthy is my network?"- When deciding where to invest relationship energy- Before planning outreach for the week- When feeling like you're losing touch with your network## How It Works1. Call `get_relationship_strength_statistics` for the network summary, including the average score and contact count by grade2. Call `get_relationship_strengths` with the Weak grade filter and `limit: 100`, then repeat with the Dormant grade filter, to build the ranked needs-attention list without scanning every contact3. For the handful of contacts included in the report, use `get_contact` and `get_contact_interactions` to explain why the relationship needs attention and suggest a specific action4. Analyze the global network with `get_global_network` for cluster and relationship patterns5. For a single-contact health check, call `get_relationship_strength` and supplement it with contact details and interactions as needed## Health ScoringEvergreen calculates relationship strength scores from 0–100 based on recency,frequency, depth, and variety of interactions. Use the score returned by therelationship-strength tools rather than calculating or weighting these factorsin the skill.## Health Grades| Grade | Score | Action ||-------|-------|--------|| Strong | 80–100 | Maintain current pace || Good | 60–79 | No action needed || Moderate | 40–59 | Consider a check-in || Weak | 20–39 | Prioritize outreach this week || Dormant | 0–19 | Re-engagement needed |## Example Output```markdown## Network Health Report — April 2026### Summary- **Total active contacts:** 127- **Strong:** 12 (9%)- **Good:** 34 (27%)- **Moderate:** 28 (22%)- **Weak:** 18 (14%)- **Dormant:** 35 (28%)### Needs Attention (Top 5 Weak or Dormant)1. **Marcus Webb** (Founder, DataFlow) — Weak, score 38. Was very active (4 interactions in Q1). Partnership proposal pending.2. **Lisa Park** (VP Product, Meridian) — Weak, score 35. Procurement discussion stalled. You owe security questionnaire.3. **David Kim** (DataTech) — Weak, score 32. Key introducer in your network (introduced 4 contacts). Worth maintaining.4. **Rachel Torres** (Angel investor) — Dormant, score 18. Offered to help with hiring, never followed up.5. **Tom Bradley** (Advisor) — Dormant, score 15. Quarterly coffee overdue.### Network Insights- Your most active cluster: Atlanta AI community (23 contacts, avg 18 days between interactions)- Weakest cluster: College network (15 contacts, avg 140 days between interactions)- Top introducer going dormant: David Kim — maintain this relationship- You have 8 contacts with pending actions older than 2 weeks```## Checklist```Relationship Health:- [ ] Relationship strength statistics summarized- [ ] Strong, Good, Moderate, Weak, and Dormant grades reported- [ ] Weak and Dormant relationships prioritized by value- [ ] Specific action suggested for each Weak or Dormant contact- [ ] Network-level insights provided (clusters, trends)- [ ] Pending stale actions flagged```## Learn More- [Evergreen — Local-First Personal CRM](https://heltonlabs.com/evergreen)- [Vibe Coding a Personal CRM](https://mcginniscommawill.com/posts/2025-09-05-vibe-coding-personal-crm/)- [Evergreen Gets Even Evergreener](https://mcginniscommawill.com/posts/2026-01-26-evergreen-gets-even-evergreener/)

Frequently asked questions