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Agent Skill · 研究检索

archive-conversation(存档对话)

archive-conversation 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。

archive-conversation 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 36,459。

总安装 1,922周安装 77GitHub Stars 2下载 622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

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:archive-conversation(存档对话)
来源仓库:https://github.com/nweii/agent-stuff
仓库路径:skills/archive-conversation
安装命令:
npx skills add https://github.com/nweii/agent-stuff --skill archive-conversation
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/nweii/agent-stuff --skill archive-conversation

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。

用于创建 AI 对话的归档摘要,捕捉思维演进过程。支持技术工作会话和创意探索等不同类型对话分析。提供概念线程追踪和突破点识别等专业能力。archive-conversation 属于研究检索类 Skill,可作为该场景下的辅助能力补充。安装需从指定 GitHub 仓库获取,使用时需完整阅读对话内容。

涉及知识保存时应确认存储位置和访问权限。

来源仓库内路径:skills/archive-conversation

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/nweii/agent-stuff --skill archive-conversation;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

archive-conversation 怎么安装?

在终端执行 npx skills add https://github.com/nweii/agent-stuff --skill archive-conversation。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

archive-conversation 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

archive-conversation 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

archive-conversation 是免费的吗?

来源标注的许可证是 MIT。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。

archive-conversation 用的人多吗?

公开数据是累计安装 1,922 次,近一周安装 77 次,下载 622 次,GitHub 2 星。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。

archive-conversation 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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 Codex,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

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
archive-conversation

存档对话 · 本页

1,9222只读MIT通过

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

AI Conversation Archival Summary

Create an archival summary of an AI conversation that captures its intellectual journey, key insights, or technical work session logs. Document either how thinking evolved throughout the discussion or the specific actions and technical decisions made during a work session.

Deep Analysis Requirements

Conduct a thorough analysis of the entire conversation:

  1. Read through completely first, identifying all conceptual threads, task sequences, and transitions
  2. Note patterns in questioning, resistance points, breakthrough moments, or technical hurdles
  3. Identify the conversation's nature (technical work session, creative exploration, strategic planning, philosophical inquiry, etc.)
  4. Understand what made this particular exchange worth preserving (insight-driven vs. action-documentation)
  5. Determine what structure would best capture its unique value (narrative vs. log-formatted)

Look deeply for:

  • The real question beneath the initial question
  • How the problem space was redefined or the technical path was forged
  • Moments where assumptions were challenged or implementation details were decided
  • Conceptual frameworks or technical patterns that emerged organically
  • The emotional/intellectual journey or the step-by-step progress of a work session
  • Valuable tangents or "failed" approaches that taught something or informed the final code
  • Connections made between seemingly unrelated ideas or system components
  • What remained intentionally unresolved or deferred to later tasks

Creating Descriptive Structure

Instead of using generic headings like "Initial Question" or "Key Findings," create headings that describe the actual content of each section. The heading should give readers immediate context about what happened in that part of the conversation.

Examples of descriptive headings:

  • "Starting from hourly vs. project pricing questions"
  • "Why the recursive function kept hitting memory limits"
  • "Exploring whether this needs to be real-time"
  • "The confusion about state management"
  • "Deciding between complexity and maintainability"

Use sentence-case for headings, not title case. Avoid marketing-speak, dramatic phrasing, or trying to be clever.

Flexible Documentation Approaches

Let the conversation's natural flow determine your structure:

For Problem-Solving Sessions: Open with what broke/what problem triggered the conversation → Document failed approaches if instructive → Describe the working solution → Note implementation details or next steps

For Creative Explorations: Start with the initial vision or desire → Show how ideas evolved or branched → Capture key decisions and why they were made → Preserve unexplored directions worth revisiting

For Learning Journeys: Begin with what the user didn't understand → Track how understanding built piece by piece → Highlight breakthrough moments → List remaining questions

For Work Sessions & Implementation Logs: Define the session's objective → Document specific actions taken and files modified → Capture technical hurdles and how they were resolved → Summarize the current state of the work and remaining tasks

For Strategic Thinking: Frame the decision that needed making → Explore options considered and their trade-offs → Document the framework or criteria that emerged → Capture action items or next considerations

Excerpt Guidelines

Include conversation excerpts that show thinking in action:

[User's first name, if known]: "[moment of recognition or confusion]" AI: "[response that shifted understanding or articulated key insight]"

Choose excerpts that reveal intellectual movement - the moments where thinking actually changed, not just where information was exchanged. Be generous in your excerpt lengths.

File Output Requirements

Naming Convention

  • Format: {{Type}} - {{topic}} YYYY-MM.md
  • Use Thinking for insight-heavy journeys or Log for action-leaning work sessions
  • Example: Thinking - Portfolio strategy 2025-08.md
  • Example: Log - Refactoring auth middleware 2025-01.md

Save Location Logic

  1. If save-location argument provided: Use that path directly
  2. Context-aware detection: Analyze the existing folder structure to find the most relevant folder for the note being archived (e.g., matching "Working" or "Journaling" folders to the conversation type).
  3. If no context: Ask the user to confirm where to save
  4. Fallback: If vault access unavailable (mobile/restricted), output as markdown code block for manual saving

Metadata

  • Add appropriate tags (e.g., #thinking, #log, #journal, #learning, #ai-chat) based on the user's system
  • Use third person or neutral documentation style, not first person (except when quoting)

Remember

  • You're documenting intellectual exploration OR technical execution/work sessions
  • Perform deep analysis to identify all important threads, transitions, and task sequences
  • Use headings that describe what actually happened or what was achieved in that section
  • Keep language natural and straightforward - no marketing-speak or forced drama
  • Capture why this journey or work session matters, and what was actually produced or decided
  • Include the messy, human elements - confusion, recognition, technical frustrations, breakthroughs
  • Preserve what would be valuable to revisit months or years later
  • When using specific examples repeatedly, vary phrasing or generalize after first mention

平台分布

Claude Code

31.27%
按下载量换算194

windsurf

22.59%
按下载量换算141

trae

20.4%
按下载量换算127

OpenCode

11.62%
按下载量换算72

Codex

8.18%
按下载量换算51

Antigravity

3.93%
按下载量换算24

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

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