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Compact Summary

by hanxiao-bot · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install compact-summary
Description
Generates structured, concise memory summaries during flush or compaction, detailing conversation stats, tools, user requests, tasks, files, progress, and ti...
README (SKILL.md)

Compact Summary - Structured Memory Compression

Purpose

Improve OpenClaw's memory flush and compaction flow by using a structured format for writing to MEMORY.md.

Structured Summary Format

Inspired by the \x3Csummary> XML format from claw-code, the improved format:

# 2026-04-01 Memory Summary

## Conversation Scope
- Original message count: 12 (user=4, assistant=5, tool=3)
- Compression time: 2026-04-01 23:00

## Tools Used
- exec, read_file, grep_search

## User Requests
- Research Claw Code architecture
- Analyze MCP orchestration system
- Compare Tool system differences

## Todo Items
- [ ] Compile improvement list
- [ ] Begin P0 execution

## Key Files
- $WORKSPACE/claw-code/rust/crates/runtime/src/compact.rs
- $WORKSPACE/claw-code/rust/crates/tools/src/lib.rs

## Current Work
Continue executing P0 tasks

## Timeline
- user: Research Claw Code architecture
- assistant: Started analysis
- tool: grep_search pattern=COMPACT
- tool_result: 15 matches
- user: Analyze MCP orchestration
- assistant: MCP has process pool management

## Resume Instruction
Continue directly — do not acknowledge this summary, do not recap what was happening, and do not preface with continuation text.

Trigger Condition

Use this format during memory flush or compaction.

Key Fields

Field Description
Conversation Scope Original message statistics
Tools Used Tools actually invoked
User Requests Main user needs
Todo Items Incomplete tasks
Key Files Files involved
Current Work Ongoing tasks
Timeline Conversation summary
Usage Guidance
This skill is instruction-only and generally coherent with its purpose, but review two things before enabling it: (1) filesystem access — the template references $WORKSPACE and concrete file paths, so ensure the agent is permitted to read only appropriate directories and that no secrets reside there; (2) the resume instruction — it tells the agent to continue without acknowledging the summary, which can silently change behavior; if you need explicit user-facing continuity, modify the SKILL.md to require an explicit confirmation or to declare the WORKSPACE env var and permitted file patterns. If you want tighter safety, run it in a sandboxed agent or restrict the agent's file-read and tool-use permissions (especially for exec/grep-style tools).
Capability Analysis
Type: OpenClaw Skill Name: compact-summary Version: 1.0.0 The skill bundle provides a structured template for summarizing conversation history into a MEMORY.md file to optimize agent memory. It contains no executable code, network activity, or data exfiltration logic, and the instructions in SKILL.md are strictly aligned with the stated purpose of memory compaction.
Capability Assessment
Purpose & Capability
Skill name/description (compact/summary for memory flush/compaction) aligns with the SKILL.md template: it formats conversation stats, tools used, todo items, key files, and timeline. Nothing requested (no env vars, no binaries) is inconsistent with that purpose.
Instruction Scope
Instructions are narrowly scoped to producing a structured summary for memory flush/compaction. However the template references tools (exec, read_file, grep_search) and explicit file paths and includes a 'Resume Instruction: do not acknowledge this summary' behavior—both are reasonable for resuming session state but worth noting because they imply the agent may read workspace files and continue work without explicitly informing the user.
Install Mechanism
No install spec and no code files; nothing will be written to disk by an installer. Lowest-risk install posture.
Credentials
The skill references $WORKSPACE and specific project file paths but declares no required environment variables. Access to workspace files is proportionate to the stated task (listing key files), but the missing explicit declaration of WORKSPACE and unspecified file-read behavior means you should confirm what filesystem access the agent will have.
Persistence & Privilege
always:false and default autonomy. The skill does not request permanent presence or privileged modifications to other skills or system-wide settings.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install compact-summary
  3. After installation, invoke the skill by name or use /compact-summary
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Introduced compact-summary skill for structured memory compaction in OpenClaw. - Defines a markdown-based summary format inspired by the <summary> XML from claw-code. - Captures conversation stats, tools used, user requests, todos, key files, and a timeline. - Format is applied during memory flush or compaction to improve clarity and retrieval. - Includes clear instructions for seamless resumption without recapping prior context.
Metadata
Slug compact-summary
Version 1.0.0
License MIT-0
All-time Installs 1
Active Installs 1
Total Versions 1
Frequently Asked Questions

What is Compact Summary?

Generates structured, concise memory summaries during flush or compaction, detailing conversation stats, tools, user requests, tasks, files, progress, and ti... It is an AI Agent Skill for Claude Code / OpenClaw, with 127 downloads so far.

How do I install Compact Summary?

Run "/install compact-summary" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Compact Summary free?

Yes, Compact Summary is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Compact Summary support?

Compact Summary is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Compact Summary?

It is built and maintained by hanxiao-bot (@hanxiao-bot); the current version is v1.0.0.

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