PO Service Completion Evidence Gap
Check your service invoices and completion records for missing supporting records.
Purchase order matching
Recheck the figures in your supplied tolerance policy and mismatches against the rules you supply.
A downloadable skill for your AI agent.
Documented exception calculations.
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.
Supplied tolerance policy and mismatches. 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 PO Tolerance Rule Evidence Sheet skill. Review the attached records: supplied tolerance policy and mismatches. Prepare this result: documented exception calculations. 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 records the rule and the values used in each calculation. It works out the expected amount and compares it with the reported amount.
Supplied tolerance policy and mismatches.
For this task, keep one review row for each invoice variance + tolerance rule. Record allowed amount, percentage base, and actual variance. Keep the source location beside each value.
Trace partial receipts, split invoices, deposits, returns, credits, and amendments. Distinguish quantity variance from price variance.
Use supplied tolerances and unit conversions. A three-way match is evidence for review, not payment authorization.
The helper validates arithmetic, not the legal or business rule. It does not infer a formula, evaluate spreadsheet functions, or round silently. Use a sourced tolerance for rounding comparisons.
This synthetic example shows the included check in use. Your agent uses its findings to complete your task report.
Synthetic example records
| Sample record | expression: quantity * rate; variables: quantity: 4; rate: 25.00; observed: 101.00; unit: example units |
|---|
A difference needs review
This result comes from the checking tool in your download.
These are synthetic records from the bundled example.
Synthetic rule: amount = quantity * rate; no tolerance. Not customer evidence.{"expression": "quantity * rate", "id": "r1", "key": "invoice variance + tolerance rule / SYNTHETIC-001", "observed": "101.00", "rule_source_id": "rule", "unit": "synthetic-unit", "variables": {"quantity": "4", "rate": "25.00"}}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 supplied tolerance policy and mismatches. Confirm the case, period, and source versions before the review.
Use supplier, PO, line, receipt, invoice revision, unit to keep records distinct. The agent records the original value, an exact quote, and the source location.
Apply the supplied formula and compare the calculated amount with the reported amount. Run the Python helper on the structured records. Check each finding against its source.
Prepare the task result: documented exception calculations. 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.