By name: update-dashboard description: Update dashboard.yaml with current knowledge base metrics from analysis report disable-model-invocation: true user-invocable: true allowed-tools: - Read - Write - Bash - Glob
Update Dashboard
Refresh the Trinity dashboard with current knowledge base metrics extracted from the analysis report.
Output Location
Write to: /home/developer/dashboard.yaml
STEP 1: Read Analysis Report
Read knowledge-base-analysis.md from the project root
Extract the following metrics using regex or line parsing:
Core Metrics (from header section, lines 4-5)
- Analysis Date: Pattern
**Analysis Date:** YYYY-MM-DD - Total Notes: Pattern
**Total Notes:** X,XXX - Blocks: Pattern
**Blocks:** XX,XXX - Permanent Notes: Pattern
**Permanent Notes:** XXX - AI Insights: Pattern
**AI Insights:** XXX - Document Insights: Pattern
**Document Insights:** XXX
From Summary Table (lines 14-25)
- Document Sessions: From table row
- MOCs: From table row
- Changelogs: From table row
- Source notes: From table row
- Output pieces: From table row
- Change values: The "+XX" column for trends
From Domain Distribution (lines 389-398)
- AI/Agents: XX%
- Neuroscience/Dopamine: XX%
- Buddhism/Consciousness: XX%
- Decision-Making/Biases: XX%
- Identity/Belief Systems: XX%
- Business/Content Marketing: XX%
- Flow/Performance: XX%
From Statistics (lines 383-385)
- Original frameworks: Count
STEP 2: Build Dashboard YAML
Construct the dashboard with gathered values:
title: "Cornelius Knowledge Base"
refresh: 300
sections:
- title: "Knowledge Base Overview"
layout: grid
columns: 3
widgets:
- type: metric
label: "Total Notes"
value: {total_notes}
trend: up
trend_value: "{notes_change}"
description: "All notes in vault"
- type: metric
label: "Total Blocks"
value: {total_blocks}
trend: up
trend_value: "{blocks_change}"
description: "Content blocks indexed"
- type: text
content: "Last Analysis: {analysis_date}"
size: small
color: gray
- title: "Note Categories"
layout: grid
columns: 3
widgets:
- type: metric
label: "Permanent Notes"
value: {permanent_notes}
trend: up
trend_value: "{permanent_change}"
description: "Atomic insights"
- type: metric
label: "AI Insights"
value: {ai_insights}
trend: up
trend_value: "{ai_change}"
description: "AI-extracted notes"
- type: metric
label: "Document Insights"
value: {document_insights}
trend: up
trend_value: "{doc_change}"
description: "Research extracts"
- type: metric
label: "MOCs"
value: {mocs}
trend: up
trend_value: "{mocs_change}"
description: "Navigation hubs"
- type: metric
label: "Source Notes"
value: {source_notes}
description: "Books & articles"
- type: metric
label: "Output Pieces"
value: {output_pieces}
trend: up
trend_value: "{output_change}"
description: "Published content"
- title: "Domain Distribution"
layout: grid
columns: 2
widgets:
- type: progress
label: "AI/Agents"
value: {ai_percent}
color: blue
- type: progress
label: "Neuroscience/Dopamine"
value: {neuro_percent}
color: purple
- type: progress
label: "Buddhism/Consciousness"
value: {buddhism_percent}
color: green
- type: progress
label: "Decision-Making"
value: {decision_percent}
color: orange
- type: progress
label: "Identity/Belief"
value: {identity_percent}
color: yellow
- type: progress
label: "Business/Marketing"
value: {business_percent}
color: gray
- title: "Growth & Activity"
layout: grid
columns: 4
widgets:
- type: metric
label: "Document Sessions"
value: {doc_sessions}
description: "Research sessions"
- type: metric
label: "Original Frameworks"
value: {frameworks}
description: "Custom models"
- type: metric
label: "Changelogs"
value: {changelogs}
description: "Activity records"
- type: text
content: "Phase: Technical Implementation"
size: small
color: blue
- title: "Seven Thematic Hubs"
layout: list
widgets:
- type: list
title: "Primary Knowledge Domains"
items:
- "Consciousness & Self (Buddhism-Neuroscience Bridge)"
- "Dopamine & Motivation (Master Hub)"
- "Decision-Making & Cognitive Biases"
- "Identity & Belief Systems"
- "AI Agents & Digital Intelligence (Largest - 546 notes)"
- "Flow States & Peak Performance"
- "Business & Content Marketing Psychology"
style: bullet
max_items: 7
STEP 3: Parse Metrics from Report
Use the following extraction logic:
For header metrics (line 5):
Pattern: **Total Notes:** (\d+,?\d*) | **Blocks:** (\d+,?\d*) | **Permanent Notes:** (\d+) | **AI Insights:** (\d+) | **Document Insights:** (\d+)
For table metrics (lines 14-25):
Look for lines with | Total notes | X,XXX | +XXX |
Extract value and change columns
For domain percentages (lines 389-398):
Pattern: AI/Agents.*:\s+(\d+)%
Pattern: Neuroscience.*:\s+(\d+)%
etc.
STEP 4: Write Dashboard
Write the constructed YAML to /home/developer/dashboard.yaml
Ensure:
- All numeric values are integers (no commas in YAML)
- Percentages are integers without % symbol
- Trends use "up" or "down" based on change values
- Date is in YYYY-MM-DD format
STEP 5: Confirm Update
Report what was updated:
Dashboard updated at {current_timestamp}
Metrics refreshed:
- Total Notes: {value} ({change})
- Permanent Notes: {value} ({change})
- AI Insights: {value} ({change})
- Document Insights: {value} ({change})
- Domain distribution: AI {X}%, Neuro {X}%, Buddhism {X}%...
Dashboard written to: /home/developer/dashboard.yaml
Scheduling
This skill can be scheduled via /trinity-schedules:
# Daily update (recommended)
/trinity-schedules add update-dashboard --cron "0 9 * * *"
# After each /analyze-kb run
Run manually: /update-dashboard
Note: Dashboard data is only as fresh as the last /analyze-kb run. Consider running analyze-kb before update-dashboard for accurate metrics.