Agency Deliverable Format Expansion
Check your agreed formats and latest requests for missing supporting records.
Agency scope control
Bring conflicting details in your approval matrix and stakeholder messages into one review.
A downloadable skill for your AI agent.
Unlisted approver decisions.
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.
Approval matrix and stakeholder messages. 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 Client Signoff Authority Conflict skill. Review the attached records: approval matrix and stakeholder messages. Prepare this result: unlisted approver decisions. 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 statements about the same item. Different values stay visible together, with their original sources.
Approval matrix and stakeholder messages.
For this task, keep one review row for each deliverable + approval authority. Record named approver, stakeholder decision, and delegated scope. Keep the source location beside each value.
Compare requests and delivered work with the exact signed scope. Preserve exclusions, revision definitions, stakeholder authority, and acceptance evidence.
Do not infer that feedback authorizes extra billing. Record ambiguous revision versus new-deliverable cases for client review.
The engine does not decide which source has authority. Establish that from supplied records and flag unresolved authority.
This synthetic example shows the included check in use. Your agent uses its findings to complete your task report.
Synthetic example records
| Sample record | named approver: assertion-A |
|---|---|
| Sample record | named approver: assertion-B |
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": "deliverable + approval authority / SYNTHETIC-001", "value": {"named approver": "assertion-A"}}{"id": "r2", "key": "deliverable + approval authority / SYNTHETIC-001", "value": {"named approver": "assertion-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 approval matrix and stakeholder messages. Confirm the case, period, and source versions before the review.
Use client, project, deliverable, SOW revision, approval to keep records distinct. The agent records the original value, an exact quote, and the source location.
Group records by item and identify different supplied values. Run the Python helper on the structured records. Check each finding against its source.
Prepare the task result: unlisted approver decisions. 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.