Use the local AI usage,
Organized into a submission package.

I want to do a cost checkup, but I don’t know how to prepare the materials?
Use TuneMeter to collect dosage, follow the manual to export and check, and then submit it to Tunenomics for verification and analysis.

01 Select range Only collect the sources and dates you selected
02 Look at desensitization Check submission package and known data gaps
03 Do a checkup Submit on your own initiative and return to the original task to receive the report

Follow the manual Get TuneMeter (new window)

v 3.3.5 Pre-release version · If you already have a bill or usage meter, you can also directly Enter checkup

Follow along / An operation manual

From the usage of the machine, to an analysis report.

Export first, then submit. Divide it into two chapters and do one step at a time.
The left and right direction keys can also turn pages, and the content will not automatically jump away.

FIELD GUIDE / EXPORT 01 / 08

Download CLI and unzip it completely

Open the official release page and select CLI ZIP. Unzip the entire folder and run it in the unzipped directory; it is not necessary to install the Agent Skill first.

Prepare tunemeter.pyz and package instructions.

Operation instructions Not reading your device

TuneMeter CLI

v 3.3.5 · Pre-release version

Download CLI ZIP (new window)Version notes and verification files This is the program package; the "Tuninomics submission package.zip" generated after running is the checkup material.

A / Local preparation One page at a time, at your own pace.

Page 1 / 8 · Get Tools

Nine types of known format adapters have been implemented, and compatibility is affected by the client format; the direct verification environment is Windows 11 / Python 3.12.14, which cannot be regarded as full platform or version certification.View support range

Public development / 01

TuneMeter, start with specific problems.

is maintained by Tunenomics, and the code and version are public.
The scope and limitations of capabilities are also clearly stated.

TuneMeter

Tunenomics Dosage Meter · by Tunenomics

Tunenomics self-developed/CLI

Collect the usage from the known Agent records of the local machine and generate a submission package with default desensitization. The tool is only responsible for collection and does not convert Tokens into actual consumption.

Local collection
Choose the source and date yourself, and leave gaps clearly.
01
Default desensitization
Submit package excludes body, original path and session details.
02
Generate a submission package
Review the "Turenomics submission package.zip" and then actively submit for checkup.
03

v 3.3.5 · Pre-release Python 3.10+ · No additional running dependencies

Scope of use and support

GitHub Repository Public

imxiaowho /tunenomics-tunemeter

offline-usage redacted-bundle

Stars 0 ⑂ Forks 0(new window)

Python·MIT

Stars and Forks are 2026-10-21 Check the snapshot and click to view the current status. v 3.3.5 is a pre-release version; attention does not represent verification conclusions.

Source code, version and maintenance records(new window)

From tools to delivery

You control the material and leave the analysis to Tunenomics.

Let’s look at the delivery report first

01 / Ready

Submit reviewed materials

TuneMeter submission package, or existing PDF, CSV, Excel. Explain the source, date and problem you want to solve, and submit it proactively after logging in.

02 / Want to know first

See clearly what the data can explain

Collection package reflects observed usage. Actual expenses still require corresponding evidence, and subscription payments cannot be calculated based on Token alone; the report will explain the measurement basis and limitations.

Communicate the scope of analysis first

Checkup supports PDF / CSV / Excel / ZIP, a single file does not exceed 20 MB. Please review the desensitization instructions before submitting your ZIP. TuneMeter does not read account credentials and does not automatically upload; when the report is opened and given to the cloud agent for reading, the selected content may still be passed to the model service.