Use when recording work sessions, tracking decisions and outcomes, or documenting lessons learned
version
1.1
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]
: ~XX,XXX
---
| 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 |
| ... | ... | ... | ... |
:
High-attention task time: X% (mainly XX:XX-XX:XX)
Interruptions/switches: X
Peak efficiency period: XX:XX-XX:XX
---
: [Core outcome or decision]
:
[Specific data/numbers]
[File paths/names]
[Decision rationale]
[Verification results]
(if applicable):
[Key takeaways]
---
| 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] |
---
[HH:MM-HH:MM] [Task name] - [Status]
[HH:MM-HH:MM] [Task name] - [Status]
---
| 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 |
---
: [Core lesson]
: [What happened]
: [Why it happened]
: [How to improve]
---
- [One-sentence description]
- [One-sentence description]
---
-
**Token Consumption**
## ⏱️ Time Distribution
**Time Analysis**
-
-
-
## 🎯 High-Attention Tasks (Weight 8-10)
### [Task Name] (Weight: X/10, Time Slot: HH:MM-HH:MM, Duration: X min)
**One-sentence Summary**
**Key Details**
-
-
-
-
**Lessons Learned**
-
## 📋 Medium-Attention Tasks (Weight 5-7)
## 📝 Low-Attention Tasks (Weight 0-4)
-
-
## 📊 Today's Statistics
## 💡 Today's Biggest Lesson
**One-sentence Summary**
**Background**
**Root Cause**
**Improvement Measures**
## 🔗 Key File Locations
### High-Value Outputs
-
`path/to/key/file1`
-
`path/to/key/file2`
*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
