A smart conversation compression tool that preserves deep technical context and project intent when LLM context windows reach their limits.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install lobster-compact
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install lobster-compact using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Lobster Compact?
Lobster Compact is a specialized utility within the Openclaw Skills ecosystem designed to manage long-form developer conversations. As AI interactions scale, context windows can become cluttered or hit token limits, leading to a loss of critical project details. This skill intervenes by performing a chronological analysis of the exchange, distilling complex technical decisions into a structured summary.
By synthesizing user intent, technical patterns, and feedback, the skill ensures that the AI agent maintains a high-fidelity understanding of the project trajectory. It doesn't just shorten text; it extracts the technical essence of the work, including file names, function signatures, and specific bug fixes, ensuring seamless continuity in long-term development cycles.
Lobster Compact Use Cases
- Managing long-running coding sessions where the context window is nearing its limit.
- Transitioning between different phases of a project while keeping critical technical decisions visible.
- Manually triggering a summary using the /compact command to clear mental overhead.
- Consolidating multi-turn debugging sessions into a single reference point for the AI agent.
How Lobster Compact Works
- Chronological Analysis: The skill scans the entire conversation history to identify core requests, technical concepts, and code patterns.
- Context Extraction: It specifically targets high-value data such as file names, function signatures, and previously resolved errors.
- Structured Generation: A detailed Markdown summary is created covering primary intents, technology stacks, user feedback, and pending tasks.
- Memory Synchronization: The skill integrates with memory tools to update MEMORY.md and daily logs, preventing information loss across sessions.
- Validation: The process concludes once the summary captures all critical context and the long-term memory files are successfully updated.
Lobster Compact Setup
To integrate this skill into your workflow, ensure your environment supports Openclaw Skills and install the compact package via your CLI:
# Install the lobster-compact skill
openclaw install lobster-compact
# Manual trigger in conversation
/compact
Lobster Compact Data Schema & Taxonomy
The skill organizes summarized data into a highly structured taxonomy within the conversation and external memory files:
| Section | Data Captured |
|---|---|
| Technical Concepts | Frameworks, libraries, and architectural tools used. |
| Files & Code | Specific file paths and critical code snippets or function signatures. |
| Fixes & Feedback | Errors encountered, their solutions, and explicit user preferences. |
| Task Pipeline | To-do lists, current active focus, and immediate next steps. |
| Memory Storage | Updates to MEMORY.md and date-stamped logs (e.g., memory/YYYY-MM-DD.md). |
Lobster Compact Advanced Features
- Auto-Trigger Mechanism: Automatically activates when the AI agent detects the context window is approaching its technical limit.
- Focused Compaction: Accepts optional arguments to focus the summary on a specific module or technical area.
- Deduplication Logic: Utilizes memory_search to ensure that summarized information does not create redundant entries in long-term storage.
- Multi-Lingual Support: Capable of processing and summarizing prompts in both English and Chinese.
SKILL.md
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