Solar Equipment Model Document Crosscheck
Compare equipment models across solar project documents and find identifiers that do not match.
Solar project administration
Find where your utility form and supplied account record disagree.
A downloadable skill for your AI agent.
Inconsistent identity fields.
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.
Utility form and supplied account 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 Solar Interconnection Customer-Name Match skill. Review the attached records: utility form and supplied account record. Prepare this result: inconsistent identity fields. 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 records for the same item side by side. It keeps both original values when they differ, so you can check the source.
Utility form and supplied account record.
For this task, keep one review row for each project + customer-name field. Record utility account name, application name, and identifier. Keep the source location beside each value.
Crosscheck identifiers across approved plans, datasheets, utility forms, inspection records, and final handover. Preserve every rejection comment and response.
Use the authority's supplied checklist. A complete packet is not an engineering approval, permit, or permission to operate.
A changed value does not show which source is correct. Semantic equivalence and identity aliases need an explicit mapping and review.
This synthetic example shows the included check in use. Your agent uses its findings to complete your task report.
Synthetic example records
| Starting record | utility account name: source-A |
|---|---|
| Record to check | utility account name: source-B |
A difference needs review
This result comes from the checking tool in your download.
These are synthetic records from the bundled example.
{"id": "e1", "key": "project + customer-name field / SYNTHETIC-001", "value": {"utility account name": "source-A"}}{"id": "o1", "key": "project + customer-name field / SYNTHETIC-001", "value": {"utility account name": "source-B"}}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 utility form and supplied account record. Confirm the case, period, and source versions before the review.
Use project address, utility account, permit, equipment model, plan revision to keep records distinct. The agent records the original value, an exact quote, and the source location.
Match each item, then compare its supplied values. Run the Python helper on the structured records. Check each finding against its source.
Prepare the task result: inconsistent identity fields. 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.