Daily Log Skill

Overview

Generate comprehensive daily operation logs to track work, decisions, and lessons learned.

When to Use

Use this skill at the end of a work session or day to:

Record completed tasks and their outcomes
Track token usage and time spent
Document key decisions and their rationale
Capture lessons learned and mistakes
Maintain continuity across sessions

Log Format Templates

Template A: Full Detail (Legacy)

Use for: Important milestones, detailed project records See: FULL_TEMPLATE

Template B: Attention-Driven (Recommended)

Use for: Daily work logging, quick review See below ⬇️

Attention-Driven Log Format (v1.1)

# YYYY-MM-DD Operation Log

## 📅 Session Overview
- **Date**: YYYY-MM-DD
- **Work Period**: HH:MM - HH:MM (X hours X minutes)
- **Core Outcomes**: [One-sentence summary of the day's most important output]
- **Key Decisions**: [X]
- **Lessons Learned**: [X]
- **Token Consumption**: ~XX,XXX

---

## ⏱️ Time Distribution

| Time Slot | Task | Duration | Attention Weight |
|-----------|------|----------|-----------------|
| HH:MM-HH:MM | [Task 1] | X min | 9/10 |
| HH:MM-HH:MM | [Task 2] | X min | 7/10 |
| ... | ... | ... | ... |

**Time Analysis**:
- High-attention task time: X% (mainly XX:XX-XX:XX)
- Interruptions/switches: X
- Peak efficiency period: XX:XX-XX:XX

---

## 🎯 High-Attention Tasks (Weight 8-10)

### [Task Name] (Weight: X/10, Time Slot: HH:MM-HH:MM, Duration: X min)

**One-sentence Summary**: [Core outcome or decision]

**Key Details**:
- [Specific data/numbers]
- [File paths/names]
- [Decision rationale]
- [Verification results]

**Lessons Learned** (if applicable):
- [Key takeaways]

---

## 📋 Medium-Attention Tasks (Weight 5-7)

| Task | Weight | Time Slot | Key Outcome |
|------|--------|-----------|-------------|
| [Task name] | 7/10 | HH:MM-HH:MM | [One-sentence description] |
| [Task name] | 6/10 | HH:MM-HH:MM | [One-sentence description] |

---

## 📝 Low-Attention Tasks (Weight 0-4)

- [HH:MM-HH:MM] [Task name] - [Status]
- [HH:MM-HH:MM] [Task name] - [Status]

---

## 📊 Today's Statistics

| Item | Value |
|------|-------|
| High-attention tasks | X |
| Medium-attention tasks | X |
| Low-attention tasks | X |
| Code files created | X |
| Code files modified | X |
| Skill created/updated | X |
| Token consumption | ~XX,XXX |
| Git commits | X |

---

## 💡 Today's Biggest Lesson

**One-sentence Summary**: [Core lesson]

**Background**: [What happened]
**Root Cause**: [Why it happened]
**Improvement Measures**: [How to improve]

---

## 🔗 Key File Locations

### High-Value Outputs
- `path/to/key/file1` - [One-sentence description]
- `path/to/key/file2` - [One-sentence description]

---

*Log generated at: YYYY-MM-DD HH:MM*  
*Attention score: High[X] Medium[X] Low[X]*

Attention Scoring System

How to Score Task Attention (0-10)

| Factor | Weight | Indicator | Examples | |--------|--------|-----------|----------| | Key Decision | +3 | Changed direction or approach | Choose plan B, approve implementation, confirm specification | | Lesson/Mistake | +3 | Discovered and fixed issues | Violate rules, compile error, logic bug | | Milestone | +2 | Important milestone completed | MVP completion, release, feature acceptance | | File Changes | +1/ea | Create/modify/delete files | Create new Skill, modify config, refactor code | | Routine Operations | 0 | Routine queries or checks | Check status, read files, check logs |

Attention Level Guidelines

Score 8-10 (High): 
  → Full detail: summary + key details + lessons
  
Score 5-7 (Medium): 
  → Brief: one sentence summary + key outcomes
  
Score 0-4 (Low): 
  → Minimal: title + status only

Examples

Task: "Design MissionSystem Architecture"

Key decision: +3 (Chose TK_SERIAL plan)
Milestone: +2 (Design completed)
Score: 8/10 → High attention

Task: "Fix Compile Error"

Lesson: +3 (Learned BinaryReader→TK conversion)
File changes: +8 files modified = +1 (max)
Score: 9/10 → High attention

Task: "Check git status"

Routine operation: 0
Score: 2/10 → Low attention

Workflow

Step 1: Review Session

At end of session/day:

List all tasks completed
Identify major decisions made
Note any mistakes or lessons
Check for milestones reached

Step 2: Score Each Task

Apply attention scoring:

For each task:
  - Did it involve a key decision? (+3)
  - Was there a mistake/lesson? (+3)
  - Was it a milestone? (+2)
  - How many files changed? (+1 per, max 2)
  - Sum → Attention Score (0-10)

Step 3: Categorize by Attention Level

High (8-10): Write detailed section
Medium (5-7): Add to table
Low (0-4): List as bullet points

Step 4: Extract Key Information

For high-attention tasks, extract:

One-sentence summary
Key details (numbers, paths, outcomes)
Lessons learned (if applicable)

Step 5: Generate Log

Write to memory/YYYY-MM-DD.md using attention-driven template

Step 6: Update Long-term Memory (Optional)

If significant decisions or patterns emerged, update MEMORY.md

Best Practices

✅ Do

Score honestly - Not every task is high attention
Focus on value - What would you want to remember in a month?
Quantify - Use numbers, file counts, token estimates
Link key files - Only high-value outputs need paths
One lesson max - Focus on the most important lesson of the day

❌ Don't

Don't over-document low-attention tasks
Don't skip lessons learned section
Don't include full conversation transcripts
Don't log routine checks (git status, etc.) unless relevant
Don't wait too long (score while memory is fresh)

Comparison: Full Detail vs Attention-Driven

Scenario: MissionSystem MVP Implementation Day

Full Detail Version: ~500 lines, ~95,000 tokens to read

Every task fully documented
All file paths listed
Complete error descriptions
Full conversation context

Attention-Driven Version: ~150 lines, ~20,000 tokens to read

2-3 high-attention tasks detailed
3-4 medium tasks in table
5+ low tasks as bullets
Key decisions and lessons highlighted

Review Time:

Full Detail: 10-15 minutes to scan
Attention-Driven: 2-3 minutes to understand

Version History

v1.1 (2026-02-12) - Added Attention-Driven logging
- Attention scoring system (0-10)
- Three-level detail format
- Focus on high-value information
- Reduced log size by 60-70%
v1.0 (2026-02-10) - Initial release
- Standardized log format
- 7-section structure
- Statistics tracking
- Lessons learned framework