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Agent Skill · 研究检索

compaction-survival(压实生存)

compaction-survival 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

compaction-survival 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 4,944。

总安装 28,813周安装 1,177GitHub Stars 公开资料未说明下载 9,228核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:compaction-survival(压实生存)
来源仓库:https://github.com/rustyorb/compaction-survival
安装命令:
openclaw skills install compaction-survival
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install compaction-survival

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

防止 LLM 压缩期间因上下文丢失导致临界状态中断。使用预写日志 (WAL) 和工作缓冲区实现自动恢复机制。保障关键操作在压缩前后的一致性与完整性。安装命令:openclaw skills install compaction-survival。需配合定期快照策略以降低数据丢失风险。

compaction-survival 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install compaction-survival;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

compaction-survival 怎么安装?

在终端执行 openclaw skills install compaction-survival。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

compaction-survival 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

compaction-survival 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

compaction-survival 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

compaction-survival 用的人多吗?

公开数据是累计安装 28,813 次,近一周安装 1,177 次,下载 9,228 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

compaction-survival 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
compaction-survival

压实生存 · 本页

28,813—需要联网MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
compaction-survival
version
1.0.0
description
Prevent context loss during LLM compaction via Write-Ahead Logging (WAL), Working Buffer, and automatic recovery. Three mechanisms that ensure critical state — decisions, preferences, values, paths — survives when the context window compresses. Always-active behavioral skill, not a one-time tool.
author
rustyorb
keywords
[memory, compaction, context, wal, write-ahead-log, session-state, persistence, survival, long-context, agent-memory]
metadata
openclaw
emoji
🛡️

Compaction Survival System

Compaction destroys specifics: file paths, exact values, config details, reasoning chains. This skill ensures critical state survives.

The problem: When your context window fills up, OpenClaw compacts older messages into a summary. Summaries lose precision — exact numbers become "approximately," file paths vanish, decisions lose their rationale. Your agent wakes up dumber after every compaction.

The fix: Three mechanisms that capture critical state before compaction hits, and recover it after.

Three Mechanisms

1. WAL Protocol (Write-Ahead Logging)

On EVERY incoming message, scan for:

  • ✏️ Corrections — "It's X, not Y" / "Actually..."
  • 📍 Proper nouns — names, places, companies, products
  • 🎨 Preferences — styles, approaches, "I like/don't like"
  • 📋 Decisions — "Let's do X" / "Go with Y"
  • 📝 Draft changes — edits to active work
  • 🔢 Specific values — numbers, dates, IDs, URLs, paths

If ANY appear:

  1. STOP — do not compose response yet
  2. WRITE — update SESSION-STATE.md with the detail
  3. THEN — respond to the human

The trigger fires on the human's INPUT, not your memory. Write what they said, not what you think.

2. Working Buffer (Danger Zone)

At 60% context utilization (check via session_status):

  1. Create/clear memory/working-buffer.md, write header:
   # Working Buffer (Danger Zone)
   **Status:** ACTIVE
   **Started:** [timestamp]
  1. Every exchange after 60%: append human's message + your response summary
  2. Buffer is a file — it survives compaction
  3. Leave buffer as-is until next 60% threshold in a new session

Location: memory/working-buffer.md

3. Compaction Recovery

Auto-trigger when:

  • Session starts with <summary> tag in context
  • You should know something but don't
  • Human says "where were we?" / "continue" / "what were we doing?"

Recovery steps (in order):

  1. Read memory/working-buffer.md — raw danger-zone exchanges
  2. Read SESSION-STATE.md — active task state
  3. Read today's + yesterday's memory/YYYY-MM-DD.md
  4. Run memory_search if still missing context
  5. Extract important context from buffer → update SESSION-STATE.md
  6. Report: "Recovered context. Last task was X. Continuing."

NEVER ask "what were we discussing?" — the buffer has the answer.

SESSION-STATE.md Format

# Session State — Active Working Memory

## Current Task
[What we're actively working on]

## Key Details
- [Specific values, paths, configs captured via WAL]

## Decisions Made
- [Decisions with rationale]

## Pending
- [What's waiting/blocked]

## Last Updated
[timestamp]

Update this file frequently. It's your RAM — the only place specifics survive between compaction events.

How It Works Together

                    ┌──────────────────────────┐
                    │    Human sends message    │
                    └────────────┬─────────────┘
                                 │
                    ┌────────────▼─────────────┐
                    │  WAL: Scan for specifics  │
                    │  Found? Write first.      │
                    └────────────┬─────────────┘
                                 │
               ┌─────────────────▼─────────────────┐
               │  Context > 60%? Buffer everything  │
               └─────────────────┬─────────────────┘
                                 │
                    ┌────────────▼─────────────┐
                    │    Respond to human       │
                    └────────────┬─────────────┘
                                 │
                        ┌────────▼────────┐
                        │  COMPACTION HIT  │
                        └────────┬────────┘
                                 │
                    ┌────────────▼─────────────┐
                    │  Recovery: Read buffer,   │
                    │  SESSION-STATE, daily log  │
                    │  → Full context restored   │
                    └──────────────────────────┘

Integration

  • Works alongside MEMORY.md (long-term) and memory/YYYY-MM-DD.md (daily logs)
  • SESSION-STATE.md = working memory for current task
  • Working buffer = emergency capture for the danger zone
  • All three layers stack: WAL → Buffer → Recovery
  • No dependencies. No API keys. Pure behavioral patterns.

Why This Works

Most "memory" solutions try to store everything forever. That's the wrong problem. The real problem is precision loss during compaction. You don't need to remember everything — you need to remember the RIGHT things at the RIGHT time.

WAL catches specifics the moment they appear. The buffer captures the danger zone. Recovery restores context after the reset. Three layers, zero dependencies, zero data leakage.


*Built by @rustyorb + S1nthetta ⚡ — Battle-tested across 30+ compaction events.*

平台分布

OpenClaw

75.13%
按下载量换算6,933

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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