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Lobster Compact
by
wangxiaofei860208-source
· GitHub ↗
· v1.0.0
· MIT-0
84
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0
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1
Active Installs
1
Versions
Install in OpenClaw
/install lobster-compact
Description
Summarize long conversations to preserve context. Automatically triggered when context window approaches limits, or manually with /compact.
README (SKILL.md)
Compact — 长会话压缩
Inputs
$args: Optional focus area for the summary
Goal
Create a detailed summary of the conversation so far that preserves all critical context for continuing work.
Steps
1. Analyze the Conversation
Chronologically analyze each exchange:
- User's explicit requests and intents
- Approach taken to address requests
- Key decisions, technical concepts, code patterns
- Specific details: file names, code snippets, function signatures
- Errors encountered and how they were fixed
- User feedback and corrections
2. Generate Summary
Write a summary with these sections:
# 会话摘要
## 1. 主要请求和意图
[用户的核心需求]
## 2. 关键技术概念
[涉及的技术、框架、工具]
## 3. 文件和代码
[涉及的文件和关键代码片段]
## 4. 错误和修复
[遇到的问题及解决方案]
## 5. 用户反馈
[用户给出的指导、纠正、偏好]
## 6. 待办任务
[尚未完成的任务]
## 7. 当前工作
[最近在做什么，精确到文件和代码]
## 8. 下一步
[紧接着应该做什么]
3. Update Memory
- Save critical long-term info to MEMORY.md
- Save today's log to memory/YYYY-MM-DD.md
- Use
memory_searchto avoid duplicates
Success criteria: Summary captures all critical context; memory files updated.
Usage Guidance
This skill appears to do what it says: summarize conversations and save those summaries to your agent's memory. Before enabling it, decide if you want full conversation details (file names, code snippets, error traces) stored persistently. Ask or configure the agent to redact secrets (API keys, passwords, private keys) before saving, confirm where memory files are stored, who can access them, and how long they are retained. If you prefer tighter control, use /compact manually rather than allowing autonomous invocation, and periodically review or prune MEMORY.md and dated memory logs.
Capability Analysis
Type: OpenClaw Skill
Name: lobster-compact
Version: 1.0.0
The lobster-compact skill is designed to summarize long conversations and preserve context by writing summaries to memory files. It uses standard file and memory tools (read, write, edit, memory_search) that are appropriate for its stated purpose, and the instructions in SKILL.md focus entirely on analyzing conversation history and organizing technical details without any evidence of malicious intent or data exfiltration.
Capability Assessment
Purpose & Capability
The name/description (conversation compaction) matches the runtime instructions: analyze exchanges, create a structured summary, and write summaries to memory files. Nothing requested (no extra env vars or binaries) is out of scope for that purpose.
Instruction Scope
Instructions explicitly require extracting file names, code snippets, errors, and other granular context and then saving them to MEMORY.md and memory/YYYY-MM-DD.md. That is consistent with a compaction skill but means the skill will persist potentially sensitive data (API keys, passwords, private code) unless the agent sanitizes or filters content first. The instructions do not include explicit redaction or sanitization steps.
Install Mechanism
No install step or code files — instruction-only. Lowest risk from installation because nothing is downloaded or written beyond the normal memory writes described in the instructions.
Credentials
No environment variables, credentials, or external config paths are requested. The allowed tools (read/write/edit/memory_search/memory_get) are aligned with the stated memory-writing behavior.
Persistence & Privilege
The skill instructs writing to persistent memory files (MEMORY.md and dated memory logs), which is expected for a compaction tool. always:false and no modifications to other skills are declared. Still, this persistence means summaries (including sensitive content) will be stored long-term — verify memory access controls and retention policies.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install lobster-compact - After installation, invoke the skill by name or use
/lobster-compact - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
lobster-compact 1.0.0 - Initial Release
- Introduces automatic and manual conversation summarization to preserve context in long chats.
- Provides a detailed, structured template for summaries (in both English and Chinese).
- Summaries capture requests, technical concepts, files, code, errors, feedback, tasks, and next steps.
- Integrates memory tools to store important context and avoid duplication.
Metadata
Frequently Asked Questions
What is Lobster Compact?
Summarize long conversations to preserve context. Automatically triggered when context window approaches limits, or manually with /compact. It is an AI Agent Skill for Claude Code / OpenClaw, with 84 downloads so far.
How do I install Lobster Compact?
Run "/install lobster-compact" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Lobster Compact free?
Yes, Lobster Compact is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Lobster Compact support?
Lobster Compact is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Lobster Compact?
It is built and maintained by wangxiaofei860208-source (@wangxiaofei860208-source); the current version is v1.0.0.
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