Repair Shop Warranty Serial Evidence
Check your parts invoice and installation record for missing supporting records.
Auto repair administration
Turn your estimate approvals and work orders into a review with clear source references.
A downloadable skill for your AI agent.
Work lacking matching approval.
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.
Estimate approvals and work orders. 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 Vehicle Repair Authorization Version Map skill. Review the attached records: estimate approvals and work orders. Prepare this result: work lacking matching approval. 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 keeps recorded facts, assumptions, and unanswered questions separate. Each item retains the evidence a reviewer needs to make a decision.
Estimate approvals and work orders.
For this task, keep one review row for each work item + authorization interpretation. Record performed scope, approved estimate, and uncertain version. Keep the source location beside each value.
Link estimate revisions, authorizations, parts, cores, insurer replies, labor, and customer payments. Preserve agreed and disputed scope separately.
Use supplied labor rules, warranty requirements, and return windows. Administrative findings do not establish repair safety or coverage.
This method checks evidence references only. Interpretation, semantic matching, causal analysis, or synthetic test design is performed by the agent and must be reviewed. No model evaluation is implied by a passing fixture test.
This synthetic example shows the included check in use. Your agent uses its findings to complete your task report.
Synthetic example records
| Sample record | claim: Synthetic observation about performed scope; classification: inferred; question: What evidence can confirm this inference? |
|---|
A reviewer must decide
This result comes from the checking tool in your download.
These are synthetic records from the bundled example.
{"claim": "Synthetic observation about performed scope", "classification": "inferred", "id": "r1", "key": "work item + authorization interpretation / SYNTHETIC-001", "question": "What evidence can confirm this inference?"}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 estimate approvals and work orders. Confirm the case, period, and source versions before the review.
Use vehicle VIN, repair order, estimate revision, part/core ID to keep records distinct. The agent records the original value, an exact quote, and the source location.
Keep each claim, its classification, and the question that needs a reviewer. Run the Python helper on the structured records. Check each finding against its source.
Prepare the task result: work lacking matching approval. 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.