name	Daily Workflow Automation
description	Automatically processes daily notes when user mentions diary entries, daily summaries, or end-of-day workflows. Extracts insights, contexts, and categorizes content from "### 🧠 Notes" sections. Use when user discusses daily notes, asks "what did I work on today", mentions end-of-day, or talks about extracting diary content.

Daily Workflow Automation

Auto-process daily notes: extract entries → classify → route to appropriate files → update trackers.

When This Runs

Auto-triggers when user:

Mentions "today's diary", "daily note", "extract content"
Asks "what did I work on today?"
Natural end-of-day: "done for today", "wrapping up", "extract today"
References "### 🧠 Notes" section

Quick Workflow

Scan daily notes in 00 - Daily/ for unprocessed files
Extract entries from ### 🧠 Notes sections
Classify each entry (Diary/Insight/Context/Idea) with AI
Analyze relevance to 24 context areas (business, tech, health, etc.)
Route to primary + secondary destinations (>80% confidence)
Transform diary narratives → factual knowledge (for context files)
Present routing plan with reasoning
Get user approval (y/n/edit)
Execute routing with cross-links
Update tracker (.extract-daily-content-tracker.json)
Smart memory detection: Suggest Serena/Graphiti updates

Entry Classification

Diary Entries

Primary: 04-resources/diary.md (always)
Secondary: [area]/diary-[area].md (if >80% confidence)
Format: Preserve original narrative with date headers

Insights

Primary: 01-areas/p-dev/insights.md (always)
Secondary: Never to context files (insights ≠ context)

Context Entries

Primary: 04-resources/context.md (always)
Secondary: Matching CLAUDE.md files (if >80% confidence)
Format: Factual bullet points (no dates, no narrative)

Ideas

Primary: 04-resources/ideas.md (always)
Secondary: Never to context files

Context Areas (24 files)

Business (8):

business/mokai/CLAUDE.md
business/mokhouse/CLAUDE.md
business/accounting/CLAUDE.md
business/crypto/CLAUDE.md
business/soletrader/CLAUDE.md
business/SMSF/CLAUDE.md
business/safia/CLAUDE.md
business/trust/CLAUDE.md

Personal Development (3):

p-dev/learning/CLAUDE.md
p-dev/mindset/CLAUDE.md
p-dev/psychedelics/CLAUDE.md

Health & Fitness (4):

health-fitness/CLAUDE.md
health-fitness/diet/CLAUDE.md
health-fitness/medical/CLAUDE.md
health-fitness/gym/CLAUDE.md

Tech (5):

tech/CLAUDE.md
tech/ableton/CLAUDE.md
tech/mac/CLAUDE.md
tech/ai/CLAUDE.md
tech/ai/research-ai/context-engineering/CLAUDE.md

Other (3):

claude-code/CLAUDE.md
harry/CLAUDE.md
people/CLAUDE.md

Diary → Context Transformation

Original diary entry:

"Today I built a Supabase database for financial tracking for MOKAI. Took forever to set up auth but got it working. Will use for invoice management."

Context file format (tech/CLAUDE.md):

- Supabase: Financial tracking database with auth
  *From:* [[04-resources/diary#25-10-19 - Sun]]
  *Related:* [[business/mokai/context-mokai]]

Context file format (business/mokai/CLAUDE.md):

- Financial tracking system: Supabase database for invoice management
  *From:* [[04-resources/diary#25-10-19 - Sun]]
  *Related:* [[tech/context-tech]]

Transformations applied:

✅ Extract topically relevant facts
✅ Rephrase to third-person
✅ Remove: dates, pronouns, temporal markers, feelings
✅ Format: Bullet points with cross-links
✅ Custom formulation for each context area

Smart Memory Detection

After extraction, detect opportunities to update memory systems:

Serena Memory Detection

Triggers: Technical patterns, workflows, commands, automation Keywords: workflow, pattern, convention, script, command, automation, process

Example:

Entry: "Created new workflow using Supabase triggers for invoice automation"

Detection:
  System: Serena
  Memory: system_patterns_and_guidelines
  Confidence: 0.87
  Update: "Invoice automation: Supabase triggers reduce manual data entry"

Graphiti Detection (3 instances)

Triggers: Strategic decisions, business events, personal insights Keywords: decided, strategy, planning, client, meeting, learned, insight, discovered

Routing:

business/mokai/* or business/mokhouse/* → graphiti-mokai
business/accounting/*, crypto/*, SMSF/* → graphiti-finance
Everything else → graphiti-personal

Example:

Entry: "Discussed the future direction of MOKAI with Jack and Brie over dinner"

Detection:
  System: Graphiti
  Instance: graphiti-mokai
  Confidence: 0.85
  Episode: "MOKAI strategic planning session with Jack and Brie discussing future business direction and growth opportunities"

File References

Daily note template: reference/templates.md
Formatting rules: reference/formatting-rules.md
Extraction script: scripts/extract_content.py <date>

MCP Integration

Serena MCP (preferred for file operations):

mcp__serena__list_dir - Find daily notes
mcp__serena__search_for_pattern - Extract ### 🧠 Notes sections
mcp__serena__find_file - Locate context files
mcp__serena__write_memory - Update Serena memories

Graphiti MCP (knowledge graph storage):

mcp__graphiti__add_memory - Store strategic insights

Use Serena for pattern matching (faster than Read tool)

Tracker System

Location: .claude/commands/.extract-daily-content-tracker.json

Tracks:

Last scan timestamp
Processed files (with modification times)
Entries processed per file
Routing decisions with confidence scores

View tracker:

cat .claude/commands/.extract-daily-content-tracker.json | jq '.processed_files | to_entries | last'

Reset tracker (force re-extraction):

rm .claude/commands/.extract-daily-content-tracker.json

Critical Rules

✅ Always preserve frontmatter (date, event) in daily notes
✅ Use Serena MCP for pattern matching (faster than Read)
✅ Deduplicate insights before storing in Graphiti
✅ Never delete original content during extraction
✅ Transform diary → factual for context files
✅ Preserve narrative for diary files
✅ Require >80% confidence for secondary routing
✅ Create cross-links bidirectionally
✅ Auto-create diary files with proper frontmatter
✅ Get user approval before memory updates

User Approval Flow

After extraction, user chooses:

[a] Update all - Update all suggested memories (confidence >0.80)

[s] Selective - Choose which memories to update:

Which memories to update? (comma-separated)

1. Serena (system_patterns_and_guidelines) - Confidence: 0.87
2. Graphiti-MOKAI (strategic planning) - Confidence: 0.85
3. Graphiti-Personal (health insight) - Confidence: 0.78

Your choice: 2

[n] Skip - No memory updates

[l] Later - Queue for end-of-day batch review

Example Workflow

User: "What did I work on today?"

Claude:

Scans 00 - Daily/ for today's note
Extracts entries from ### 🧠 Notes
Classifies each entry
Presents routing plan:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📋 Extraction Plan for [[25-10-21 - Mon]]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Entry 1: "MOKAI uses Indigenous procurement..."
  Type: Context (96% confidence)
    Reason: Factual business practice information

  Primary: 04-resources/context.md
  Secondary:
    ✓ business/mokai/CLAUDE.md (98%)
      → Direct MOKAI business strategy reference
    ✓ harry/CLAUDE.md (87%)
      → Personal Indigenous identity context

Entry 2: "Finished mixing Nintendo track..."
  Type: Diary (94% confidence)
    Reason: Daily activity log, project completion

  Primary: 04-resources/diary.md
  Secondary:
    ✓ business/mokhouse/diary-mokhouse.md (97%)
      → MOK HOUSE client project completion

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Actions: [y]es / [n]o / [e]dit / [s]kip entry

User approves: y
Executes routing with cross-links
Updates tracker
Detects memory opportunities:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🧠 Memory System Detection
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

📊 Graphiti (MOKAI):
  Episode: "MOKAI Indigenous procurement strategy"
  Confidence: 0.96
  Reason: Strategic business positioning

Would you like to update memory systems?
  [a] Update all suggested memories
  [s] Selective (choose which to update)
  [n] Skip memory updates
  [l] Later (remind me at EOD)

Troubleshooting

Issue: AI misclassifies entries

Solution: Use edit mode to correct, AI learns from patterns

Issue: Too many secondary destinations

Solution: Increase confidence threshold (currently 0.8)

Issue: Diary files not created

Solution: Verify auto-creation logic, check file permissions

Issue: Missing cross-links

Solution: Verify append operations, check for write errors

Issue: Memory detection missing opportunities

Solution: Review detection keywords, adjust confidence threshold

Issue: Wrong Graphiti instance selected

Solution: Manually specify instance in selective mode

Related Commands

Fallback: /extract-daily-content (manual trigger)
Memory: /update-serena-memory
Documentation: /report:document-system

Success Criteria

✅ Correctly classify entry types (>90% accuracy)
✅ Route to appropriate areas with good confidence
✅ Show clear reasoning for routing decisions
✅ Allow easy manual override
✅ Create valid cross-links bidirectionally
✅ Auto-create diary files with proper frontmatter
✅ Track all routing decisions
✅ Handle incremental runs efficiently
✅ Maintain file integrity across all destinations
✅ Respect >80% confidence threshold for secondary routing

Daily Workflow Automation

Install Skill

SKILL.md

Daily Workflow Automation

When This Runs

Quick Workflow

Entry Classification

Diary Entries

Insights

Context Entries

Ideas

Context Areas (24 files)

Diary → Context Transformation

Smart Memory Detection

Serena Memory Detection

Graphiti Detection (3 instances)

File References

MCP Integration

Tracker System

Critical Rules

User Approval Flow

Example Workflow

Troubleshooting

Related Commands

Success Criteria