Guest Promise Housekeeping Handoff
Check your guest message exports and cleaning brief for missing supporting records.
Short-term rental operations
Find overlapping periods in your bookings and cleaning durations.
A downloadable skill for your AI agent.
Insufficient turnover windows.
Source references, missing information, and questions to review stay with the findings.
Open your download and follow the start guide. Use an AI agent that can load skill files and run the included tools.
Bookings and cleaning durations. Confirm the case and period you want to check.
Copy the request below into your agent. Add the files and any task details it needs.
Check the findings against the original records. Choose where to save the report and follow up on open questions.
Use the Back-to-Back Stay Buffer Check skill. Review the attached records: bookings and cleaning durations. Prepare this result: insufficient turnover windows. Include a source reference for each finding. List missing information and questions that need my review. Ask me to confirm the scope and where to save the report before you start.
It puts the periods for each item in date order. It marks periods that overlap and keeps both source records for review.
Bookings and cleaning durations.
For this task, keep one review row for each property + occupied interval. Record departure, cleaning start and end, and next arrival. Keep the source location beside each value.
Separate guest promises from completed service. Join booking dates to the correct property and turnover. Retain exact image hashes when checking reuse.
Account for local time zones, laundry turnaround, access windows, and same-day occupancy. Do not infer cleaning quality from file presence.
The engine does not optimize schedules, infer travel, or check staffing ratios. It checks only supplied occupied intervals.
This synthetic example shows the included check in use. Your agent uses its findings to complete your task report.
Synthetic example records
| Sample record | start: 2026-10-31T09:00:00+00:00; end: 2026-10-31T10:00:00+00:00 |
|---|---|
| Sample record | start: 2026-10-31T09:59:59+00:00; end: 2026-10-31T11:00:00+00:00 |
A difference needs review
This result comes from the checking tool in your download.
These are synthetic records from the bundled example.
{"end": "2026-10-31T10:00:00+00:00", "id": "r1", "key": "property + occupied interval / SYNTHETIC-001", "start": "2026-10-31T09:00:00+00:00"}{"end": "2026-10-31T11:00:00+00:00", "id": "r2", "key": "property + occupied interval / SYNTHETIC-001", "start": "2026-10-31T09:59:59+00:00"}After purchase, extract the ZIP. Run these commands from the skill folder. Use a new output folder.
python3 scripts/checks.py
python3 scripts/audit.py assets/example.json \
--files-root assets/sample-files --output-dir example-result
Expected exit code: 1. Code 0 means no helper finding. Code 1 means a finding or review item. Code 2 means incomplete or invalid input.
The check uses the records you supply. Review each finding against the original documents.
Ask your agent to save the completed task report in a folder you choose. The report template includes the result, source references, missing information, and next actions.
Tonotes does not receive your work documents through this website. Documents you share with an AI service follow that service's storage settings.
US$11 includes one skill in a ZIP with 18 files. You receive the instructions and tools to run the task with your own records.
Use an agent that supports SKILL.md instructions and Python 3.10 or later with SQLite. Your AI-agent service is separate.
Start with bookings and cleaning durations. Confirm the case, period, and source versions before the review.
Use property, stay, turnover, room or task to keep records distinct. The agent records the original value, an exact quote, and the source location.
Order the periods and report overlaps for each exact key. Run the Python helper on the structured records. Check each finding against its source.
Prepare the task result: insufficient turnover windows. Include missing evidence, unresolved questions, and the next action for each open item.
Eight synthetic cases check the tool locally. Live-agent accuracy on real documents has not been tested.