These five prompts cover the main analytical jobs in a 15-minute time tracking practice. Copy, paste your log, and run them at the appropriate intervals.
Prompt 1: Weekly Entry Tagging
When to use: End of week, on your raw untagged log.
Here are my time tracking entries for this week. I logged in 15-minute
increments. Please classify each entry into one of these categories:
[paste your category list]
Return a clean table with these columns:
- Time
- Description
- Category
- P/U/I (P = planned activity, U = unplanned but you initiated it,
I = external interruption you responded to)
For any ambiguous entries, choose the best-fit category and add a brief
note in parentheses explaining your reasoning.
My log:
[paste raw entries]What you get: A structured, classified log ready for pattern analysis. The P/U/I column is the most valuable addition—after four weeks, the ratio of planned to unplanned work tells you something important about how reactive versus intentional your days are.
Prompt 2: Weekly Pattern Analysis
When to use: After tagging (Prompt 1), end of each week.
Here's my categorized time log for this week. My categories are:
[list categories with brief definitions]
My intended time allocation this week was approximately:
[e.g., "60% Client Delivery, 20% Comms, 15% Admin, 5% BD"]
Please analyze and tell me:
1. Actual hours and % by category
2. Gap between intended and actual allocation — which categories are
over and which are under?
3. Deep work analysis: how many distinct focused blocks occurred?
What was the longest? At what times of day were they?
4. Three most fragmented periods of the week (most category switches
in a short window)
5. One specific observation about this week that I should pay attention to
[paste tagged log]What you get: A structured weekly debrief that connects your intention to your reality. The gap analysis in question 2 is the highest-value output—it gives you something concrete to adjust next week.
Prompt 3: Deep Work Audit
When to use: Any time you feel like your focused work isn’t happening when or how you intend.
Here's my time log. Please identify every entry that could be classified
as focused, cognitively demanding work (writing, analysis, coding, strategy,
design — whatever applies to my role as [brief description]).
For those entries:
1. List each block with its start time, duration, and what I was working on
2. Calculate total deep work time for the week and as a % of total logged hours
3. Show the distribution by time of day — what hour ranges hold the most
deep work?
4. Identify the longest uninterrupted deep work run and what followed it
5. Flag any pattern about when deep work tends to get cut short
[paste log]What you get: A clear picture of where your deep work is actually happening. The time-of-day distribution is often the most surprising output—most people find their best work is concentrated in a narrower window than they believed.
Prompt 4: Meeting Cost Audit
When to use: Any week that felt “meeting-heavy” or when you want to understand the true cost of your calendar.
Here's my time log for the week. Please identify every meeting or
synchronous call in the log.
For each meeting:
1. Identify the entry that was the meeting itself
2. Identify any entries immediately before it that appear to be prep
(e.g., "call prep", "reviewing notes before X call")
3. Identify any entries immediately after that appear to be follow-up
(e.g., "follow-up notes", "send recap", "action items from X")
Then give me:
- Total "pure" meeting time (the calls themselves)
- Total meeting halo time (prep + follow-up)
- True meeting cost (both combined) as hours and as % of week
- The meeting with the highest total halo cost (largest ratio of
surrounding work to actual meeting duration)
[paste log]What you get: The real cost of your meeting schedule, including the invisible overhead that calendar time doesn’t capture. This prompt regularly produces numbers that change people’s approach to meeting acceptance.
Prompt 5: Monthly Retrospective
When to use: At the end of each month, after four weeks of data.
I have four weeks of 15-minute time tracking data. Here are the weekly
category summaries:
Week 1: [paste totals by category]
Week 2: [paste totals by category]
Week 3: [paste totals by category]
Week 4: [paste totals by category]
My role: [brief description]
My intended allocation: [state your target % per category]
My top priorities this month were: [list 2-3]
Please:
1. Identify any category that changed consistently across all four weeks
(trending up or down)
2. Compare average actual allocation vs. intended allocation — largest gaps
3. Identify which week was most aligned with my intended allocation and
what characterized it
4. Identify which week was least aligned and what characterized it
5. Given my stated priorities, estimate how much of my time went toward
work that directly advances them vs. maintenance/overhead vs. reactive work
6. Recommend one structural change to my schedule for next month based
on this dataWhat you get: The highest-leverage output in the entire tracking practice. The priority-alignment question in step 5 is what separates time tracking from time accounting—it connects the data to the question of whether your time is going where it needs to go.
These five prompts cover the complete workflow from raw entries to monthly strategy. Start with Prompt 1 this week, work through all five by end of month.
For the full framework these prompts fit into, see The 15-Minute Quantum Framework: AI-Assisted Time Tracking.
Frequently Asked Questions
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Do these prompts work with any AI, or only specific tools?
These prompts work with any general-purpose AI that accepts plain text input—Claude, ChatGPT, Gemini, or similar. They don't require specialized integrations or APIs. The prompt quality depends on the clarity of your log entries, not on the specific AI tool.
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How long should my log entries be before running these prompts?
Prompt 1 (tagging) can be run on any amount of entries—even a single day. Prompts 2, 3, and 4 are most useful with a full week of data (30+ entries). Prompt 5 (monthly retrospective) requires four weeks of category summary data to be meaningful.