This is an automatically generated checkpoint condensing an earlier span of the conversation to free up context. Treat the captured context as established background and build on it without restating it. Continue the task directly from the messages that follow, without acknowledging this checkpoint.
摘要模型会接收逐字回放的会话:与上次已路由请求为已遮蔽区域发送的相同系统提示词、工具 schema 与消息,后面跟随一条最终 user 消息,即下方压缩指令。会话模型绝不会看到该私有请求或其推理;只有返回文本会被存储。
##### 压缩指令(最终 user 消息)
```markdown
You are now acting as a compaction engine for this AI coding assistant. Condense the conversation ABOVE into a structured checkpoint that lets another model resume the work with no loss of essential context.
Output EXACTLY the Markdown structure below: keep every section, in order. Use terse bullets, not prose paragraphs. Write "(none)" for an empty section — never drop a section.
## Primary Request and Intent
- [the user's original and evolving goals; quote verbatim where the exact wording matters]
## Key Technical Concepts
- [technologies, frameworks, patterns, and conventions in play]
## Files and Code
- [exact path: why it matters, key changes or snippets]
## Errors and Fixes
- [error: how it was resolved, plus any related user feedback]
## Pending Tasks
- [explicitly requested work not yet completed]
## Current Work
- [precisely what was in progress at this checkpoint]
## Next Step
- [the single next action, directly in line with the most recent request, or "(none)"]
## Critical Context
- [decisions and their rationale, constraints, user preferences, open questions, data needed to continue]
Rules:
- Preserve exact file paths, commands, error strings, identifiers, and function signatures.
- Capture user feedback and explicit instructions faithfully, especially corrections.
- Do NOT mention this summarization request or that the context was compacted.
- Output only the checkpoint text: do not call any tool or take any other action.
- If the conversation already contains a <compacted-summary> block, it is a PRIOR checkpoint. Do not copy it forward verbatim: preserve still-true facts, drop stale ones, and merge newer information into a single consolidated summary under the same structure.