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chat-compactor聊天压缩器

Agent Skill

chat-compactor 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

总安装

1,069

周安装

45

GitHub Stars

125

下载量

374
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

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:chat-compactor(聊天压缩器)
来源仓库:https://github.com/zhanlincui/ultimate-agent-skills-collection
仓库路径:skills/chat-compactor
安装命令:
npx skills add https://github.com/zhanlincui/ultimate-agent-skills-collection --skill chat-compactor
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/zhanlincui/ultimate-agent-skills-collection --skill chat-compactor

简介

chat-compactor 生成面向 AI 代理的结构化会话摘要,保留决策逻辑与失败路径信息。

  • 解决人工总结丢失上下文的问题,提供断点续接所需的隐性知识说明。
  • 输出包含目标、行动、障碍与下一步计划的标准化 handoff 文档。
  • 适用于多轮对话移交与团队接力场景,提升跨会话连续性体验。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Chat Compactor

Generate structured summaries optimized for AI agent continuity across sessions.

Why This Exists

Human-written summaries and ad-hoc AI summaries lose critical context:

  • Decision rationale gets lost (why X, not Y)
  • Dead ends get forgotten (agent re-tries failed approaches)
  • Implicit knowledge isn't captured (file locations, naming conventions, gotchas)
  • State is unclear (what's done, what's pending, what's blocked)

This skill produces agent-optimized handoff documents that prime the next session.

Output Format

Generate a markdown file with this structure:

# Session: [Brief Title]
Date: [YYYY-MM-DD]
Duration: ~[X] messages

## Context Snapshot
[1-2 sentences: What project/task, what state it's in right now]

## What Was Accomplished
- [Concrete outcome 1]
- [Concrete outcome 2]

## Key Decisions & Rationale
| Decision | Why | Alternatives Rejected |
|----------|-----|----------------------|
| [Choice] | [Reason] | [What didn't work and why] |

## Current State
- **Working**: [files/features that are functional]
- **Broken/Blocked**: [what's not working and why]
- **Modified files**: [list with brief note on changes]

## Dead Ends (Don't Retry)
- ❌ [Approach that failed] — [why it failed]

## Next Steps (Prioritized)
1. [ ] [Most important next action]
2. [ ] [Second priority]

## Environment & Gotchas
- [Any setup notes, versions, quirks discovered]

## Key Code/Commands Reference
[Only if there are non-obvious commands or snippets the next session needs]

Workflow

  1. Scan conversation for: decisions, outcomes, failures, file changes, blockers
  2. Identify the "handoff moment" — what would a fresh agent need to continue?
  3. Generate structured summary using format above
  4. Save to file: session-[topic]-[date].md in project root or /home/claude/sessions/

Compaction Triggers

Invoke this skill when:

  • User says: "compact", "wrap up", "save session", "summarize for next time"
  • Context window exceeds ~50% capacity and task is ongoing
  • Before major context switches
  • End of debugging/implementation session

Quality Criteria

Good compactions are:

  • Scannable: Next agent gets orientation in <30 seconds
  • Actionable: Clear next steps, not vague summaries
  • Defensive: Dead ends documented to prevent re-exploration
  • Minimal: No fluff, every line earns its tokens

Anti-Patterns

Avoid:

  • Narrative prose ("First we tried X, then Y, then Z...")
  • Redundant context (don't repeat what's in code comments)
  • Vague summaries ("Made good progress on the feature")
  • Missing failure documentation (most valuable part!)

Example Trigger & Response

User: "Let's wrap up, compact this session"

Agent:

  1. Reviews conversation for key decisions, outcomes, failures
  2. Generates structured markdown per format above
  3. Saves to session-[topic]-[date].md
  4. Confirms: "Session compacted to session-auth-refactor-2025-01-06.md — ready for next time."

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.76%
按下载量换算100

OpenCode

24.04%
按下载量换算90

Codex

15.38%
按下载量换算58

Gemini CLI

13.54%
按下载量换算51

Antigravity

8.02%
按下载量换算30

kiro-cli

3.41%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

可写文件

该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

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。

来源信息

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