Save your main context to raise quality and cut cost — building Context Drop

说明与用途

Context Drop 将大型日志和截图从 Claude Code 主对话中隔离出来，降低令牌成本并防止工具调用错误。

问题

Using Claude Code with heavy context, ultracode fan‑outs, and large logs caused tool‑call corruption, silence, and high token costs.

结果

Context Drop reduced token costs by up to 100× for large logs, eliminated tool‑call corruption, and restored model responsiveness after marathon sessions.

工作流

• 1. Identify heavy context usage (large logs, screenshots, many agents).
• 2. Install Context Drop desktop tool.
• 3. Configure Context Drop to route raw context to a subagent.
• 4. Use /compact only for the main conversation, not for raw data.
• 5. Monitor token usage and model stability.
• 6. Adjust ultracode and effort settings per task.
• 7. Iterate to keep main context under a safe size.

证据

If I had to name the one factor most consistently present, it's context bloat.

来源

The result: the conversation snapped back toward its original size immediately after the compact

来源

By the estimate on record, reading a 20k-token log once means paying for about 85k tokens over the next 30 turns.

来源

Context Drop is a small desktop tool I built to cut exactly one habit at the root: pouring raw context directly into the main conversation.

来源