#OpenClaw #Bot Operation
Don't talk about Bot profitability without counting tokens. I connect the Session Token Meter to all official bot instances, keeping an eye on every session's tokens in/out, average response time, message density, cost, and experience at a glance.
The first thing is to create records by session. Write the session_id, group/private chat source, and bound package in the same line, and then stuff it into the dashboard. This way you can see which group consumes the most, and which customer is taking advantage of the free quota.
The second thing is to set thresholds. If the token funnel difference exceeds 20%, alert me, and check the model, context window, and cache hit rate one by one. It's better to cut off a group that mocks the robot than to spread the cost across all customers.
The third thing is to make the statistical results public to customers. Let them know why a certain package has increased in price or why we limit prompt length. A transparent meter is actually the best sales script.
Don't talk about Bot profitability without counting tokens. I connect the Session Token Meter to all official bot instances, keeping an eye on every session's tokens in/out, average response time, message density, cost, and experience at a glance.
The first thing is to create records by session. Write the session_id, group/private chat source, and bound package in the same line, and then stuff it into the dashboard. This way you can see which group consumes the most, and which customer is taking advantage of the free quota.
The second thing is to set thresholds. If the token funnel difference exceeds 20%, alert me, and check the model, context window, and cache hit rate one by one. It's better to cut off a group that mocks the robot than to spread the cost across all customers.
The third thing is to make the statistical results public to customers. Let them know why a certain package has increased in price or why we limit prompt length. A transparent meter is actually the best sales script.