different-ai/notion-crm-enrichment · Archived

rate-message

Log message outcomes (reply/no reply), analyze patterns, and update Feedback Insights in Notion. This is the learning engine of the CRM.

First seen Jun 17, 2026

Installation

$ npx skills add different-ai/notion-crm-enrichment --skill rate-message

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 21
License MIT
Default branch main
Open issues 0
Status Archived

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents claude-code

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 5,001 B
  • docs SUMMARY.md 156 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 1 installs

SKILL.md

Rate Message - Learn What Works

You track message outcomes and update the Feedback Insights page so future drafts improve over time.

Input Format

User will say something like:

  • "/rate-message Sarah replied: 'thanks for reaching out'"
  • "Sarah got back to me, she wants to chat"
  • "No reply from Sam after a week"
  • "Mark Jane's message as no reply"

Step 1: Load Configuration

Read .claude/config/workspace.json to get:

  • Messages database collection URL
  • Feedback Insights page ID

If file doesn't exist: Tell user to run /setup-crm first.


Step 2: Find the Message

Search Messages database for the lead using mcpnotionnotion-search:

query: [lead_name]
data_source_url: [messages collection URL from config]

Find the most recent message for this lead with Result = "Pending".

If not found: Ask if they logged the message with /update-crm first.


Step 3: Update Message Result

Use mcpnotionnotion-update-page to update the message:

{
  "page_id": "[message_page_id]",
  "command": "update_properties",
  "properties": {
    "Result": "[Reply / No Reply / Meeting]"
  }
}

Also fetch the full message content for analysis.


Step 4: Update Lead Status

Find and update the lead's status based on outcome:

Outcome New Lead Status
Reply Replied
No Reply Contacted (no change)
Meeting Meeting

Use mcpnotionnotion-update-page on the lead.


Step 5: Analyze the Message

If the message got a reply, analyze what worked:

Element Analysis

Review the message against the 5-element framework:

  • Which elements were present?
  • Which were strongest?
  • Any patterns that stand out?

Pattern Detection

Look for:

  • Hook type: What opened the message?
  • Weakness style: How explicit was the vulnerability?
  • Pedestal specificity: How personalized?
  • Ask type: Binary vs open-ended?

If No Reply

Note potential issues:

  • Missing elements?
  • Generic language?
  • Too long?
  • Wrong timing?

Step 6: Update Feedback Insights (CRITICAL)

Fetch the current Feedback Insights page, then update it with new learnings.

For Replies (What's Working)

Add to "What's Working" section:

- [Pattern]: "[Example from message]" → Reply ([Date])

Example:

- Binary ask + explicit weakness: "is it X or Y? honestly stuck on..." → Reply (2024-01-15)

For No Replies (What's Failing)

Add to "What's Failing" section if you identify an anti-pattern:

- [Anti-pattern]: "[Example]" → No Reply ([Date])

Update Stats

Update the Stats section:

| Metric | Value |
|--------|-------|
| Total Messages | [+1] |
| Reply Rate | [recalculate] |
| Avg Rating | [recalculate] |

Use mcpnotionnotion-update-page with replacecontentrange to update specific sections.


Step 7: Report Results

Logged: [Reply/No Reply] from [Name]

Message Rating: [X]/10
Lead Status: [Old] → [New]

Analysis:
[What likely worked / What might have failed]

Pattern noted:
[Key learning added to Feedback Insights]

Feedback Insights updated: [Notion URL]

---

Stats:
• Total Messages: [N]
• Reply Rate: [X]%
• This message: [Above/Below] average

Batch Analysis

If user says "analyze my last 5 messages" or "what's working?":

  1. Fetch recent messages from Messages database
  2. Filter to those with outcomes (Reply or No Reply)
  3. Analyze patterns across the batch:

- Reply rate by element strength - Common patterns in successful messages - Common issues in failed messages

  1. Update Feedback Insights with aggregated learnings
  2. Present summary with actionable recommendations

Example Flow

User: Sarah replied: "hey thanks for reaching out, actually yeah we've been thinking about this"

Skill Response:

Logged: Reply from Sarah Chen

Message Rating: 8/10
Lead Status: Contacted → Replied

Analysis:
✓ Strong weakness element ("honestly stuck on...")
✓ Binary ask made it easy to respond
✓ Specific pedestal (referenced her Series A)
→ Her response confirms the pain point is real

Pattern noted:
Added to "What's Working":
- Binary ask + Series A reference → Reply (2024-01-15)

Feedback Insights updated: [Notion URL]

---

Stats:
• Total Messages: 12
• Reply Rate: 33% (4/12)
• This message: Above average (rated 8/10, avg 6.5)

Next: Would you like to book a meeting? Update with:
/rate-message Sarah meeting booked

Error Handling

Error Response
Message not found Suggest /update-crm to log first
Multiple pending messages Ask which one to update
Insights page missing Create minimal structure and continue
Can't parse outcome Ask for clarification (reply/no reply/meeting)