Incident Dependency Owner Handoff
Check your dependency actions and acknowledgements for missing supporting records.
Incident follow-up
Check dates in your closure date and monitoring record against the allowed periods.
A downloadable skill for your AI agent.
Insufficient observed period under supplied rule.
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.
Closure date and monitoring record. 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 Incident Recurrence Window Evidence skill. Review the attached records: closure date and monitoring record. Prepare this result: insufficient observed period under supplied rule. 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 checks each event against the start and end dates you supply. The report keeps events that fall outside the permitted period.
Closure date and monitoring record.
For this task, keep one review row for each action + monitoring window. Record closure, required observation period, and observed coverage. Keep the source location beside each value.
Trace each follow-up from observed incident evidence through action, implementation, and verification. Separate hypotheses from established observations.
Preserve clock skew and missing monitoring periods. Closure needs evidence for the stated acceptance condition.
No current date, business-day calendar, daylight-saving rule, or local deadline is inferred. Unsupported boundary rules require a separate documented check.
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: 2026-10-01; end: 2026-10-31; event: 2026-11-01 |
|---|
A difference needs review
This result comes from the checking tool in your download.
These are synthetic records from the bundled example.
{"end": "2026-10-31", "event": "2026-11-01", "id": "r1", "key": "action + monitoring window / SYNTHETIC-001", "start": "2026-10-01"}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 closure date and monitoring record. Confirm the case, period, and source versions before the review.
Use incident, action, owner, service, verification event to keep records distinct. The agent records the original value, an exact quote, and the source location.
Compare each event with the supplied allowed or blocked date window. Run the Python helper on the structured records. Check each finding against its source.
Prepare the task result: insufficient observed period under supplied rule. 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.