Long Conversations, Context, and Queued Messages

Managing long conversations
Use the message queue

Example application: reviewing a long report
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The longer the conversation, the more history the model needs to read. When context usage approaches the limit, earlier content may no longer be able to participate in the response. Instead of repeatedly adding a single “continue,” it is better to periodically organize the conclusions and unresolved questions.

While the model is still replying, you can add the next request to the queue. This is suitable for appending a clear follow-up action, such as “After finishing, organize it into three conclusions.” If the new message will change the direction of the ongoing task, stop the current generation first, then restate the goal.

In the figure: ① Two queued messages in the current topic; ② Resume automatic sending. After resuming, messages will continue to be sent from top to bottom.
The queue is not an automation plan. It only handles follow-up messages in the current topic; if you need something to run at a fixed time, use [Scheduled Task].
First upload the report and ask for issues to be listed by section. While the model is processing, add “organize the risk list after finishing” and “generate a checklist at the end” to the queue in order. If you need to verify the first round of results first, you can pause automatic sending; after confirming everything is correct, resume it. This way, you do not need to stay in the conversation and send messages one by one, and you can also avoid the next request being carried out before the review is finished.
First check whether the conversation is too long, whether the model was switched, and whether the key requirements appeared only once. Write stable rules into the explicit instructions for the current task; if you need long-term reuse, hand it over to an Agent prompt or skill.
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