SaaS Commit Drawdown Ledger Recheck
Check whether the amounts in your contract commitment and usage charges agree.
Subscription billing
Find possible duplicate entries in your workspace membership and billing rules.
A downloadable skill for your AI agent.
Potentially duplicated billable identities.
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.
Workspace membership and billing rules. 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 Multi-Workspace Seat Duplication Check skill. Review the attached records: workspace membership and billing rules. Prepare this result: potentially duplicated billable identities. 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 groups records with matching values. You review the proposed groups before deciding whether they describe the same event.
Workspace membership and billing rules.
For this task, keep one review row for each customer + billable identity partition. Record workspace membership, billing identity, and supplied dedupe rule. Keep the source location beside each value.
Use effective dates for seats, usage, pauses, price overrides, and credits. Preserve invoice cutoff and late-arriving events.
Require the approved proration rule, day-count convention, and rounding tolerance. Keep contract commitments separate from cash payments.
A repeated signature is a candidate duplicate. Legitimate repeat events can have the same content. Do not delete, merge, or accuse a party automatically.
This synthetic example shows the included check in use. Your agent uses its findings to complete your task report.
Synthetic example records
| Sample record | workspace membership: signature-A |
|---|---|
| Sample record | workspace membership: signature-A |
A difference needs review
This result comes from the checking tool in your download.
These are synthetic records from the bundled example.
{"id": "r1", "key": "customer + billable identity partition / SYNTHETIC-001", "value": {"workspace membership": "signature-A"}}{"id": "r2", "key": "customer + billable identity partition / SYNTHETIC-001", "value": {"workspace membership": "signature-A"}}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 workspace membership and billing rules. Confirm the case, period, and source versions before the review.
Use customer, subscription, billing period, plan version, currency to keep records distinct. The agent records the original value, an exact quote, and the source location.
Group exact matching values and report duplicate candidates. Run the Python helper on the structured records. Check each finding against its source.
Prepare the task result: potentially duplicated billable identities. 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.