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Agent Skill · 研究检索

wrap-up-ritual(结束仪式)

wrap-up-ritual 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。

wrap-up-ritual 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;许可证信息还不明确,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 55,679。

总安装 470周安装 20GitHub Stars 315下载 165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
unknown

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:wrap-up-ritual(结束仪式)
来源仓库:https://github.com/codewithmukesh/dotnet-claude-kit
仓库路径:skills/wrap-up-ritual
安装命令:
npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill wrap-up-ritual
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill wrap-up-ritual

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。

该技能提供会话结束前的信息检索与筛选功能。适用于 Codex、Claude、Cursor、Gemini CLI 中基于关键词的任务匹配。支持快速定位符合场景的候选结果。wrap-up-ritual 属于研究检索类 Skill,可作为该场景下的辅助能力补充。通过 GitHub 仓库安装,注意权限与维护状态。

建议结合原始 README 了解具体用途与调用方式。

来源仓库内路径:skills/wrap-up-ritual

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/codewithmukesh/dotnet-claude-kit --skill wrap-…;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

wrap-up-ritual 怎么安装?

在终端执行 npx skills add https://github.com/codewithmukesh/dotnet-claude-kit --skill wrap-up-ritual。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

wrap-up-ritual 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。

wrap-up-ritual 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。

wrap-up-ritual 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

wrap-up-ritual 用的人多吗?

公开数据是累计安装 470 次,近一周安装 20 次,下载 165 次,GitHub 315 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。

wrap-up-ritual 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。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
wrap-up-ritual

结束仪式 · 本页

470315只读未明确通过

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

Wrap-Up Ritual

Core Principles

  1. Sessions are ephemeral, knowledge is permanent — When a session ends, context is lost. But learnings, decisions, and progress don't have to be. The wrap-up ritual bridges the gap between sessions by writing a handoff note.
  2. Three captures every time — Every session ending captures exactly three things: what was DONE, what is PENDING, and what was LEARNED. No exceptions. Skipping any of these creates gaps for the next session.
  3. Handoff notes are written for a stranger — Write the handoff as if the next person has zero context. Include file paths, decision rationale, and specific next steps. "Continue the refactor" is useless. "Refactor src/Orders/CreateOrder.cs to use the Result pattern — see the Catalog module for the established pattern" is actionable.
  4. Consistent location, always overwritten — The handoff file lives at .claude/handoff.md. Each session overwrites the previous one — there's only ever one active handoff. Old handoffs are not valuable; current state is.
  5. Learnings flow to permanent memory — The "learned" section of a wrap-up is a trigger for the self-correction-loop skill. Any correction or discovery worth remembering should be captured in MEMORY.md as a permanent rule, not just in the ephemeral handoff.

Patterns

Session Summary Template

The handoff file follows a consistent structure:

# Session Handoff

> Generated: 2025-07-15 | Branch: feature/order-validation

## Completed
- [x] Added FluentValidation to CreateOrder command
  - File: `src/Orders/Features/CreateOrder.cs` (lines 15-35)
  - Validator checks: non-empty CustomerId, at least 1 item, positive quantities
- [x] Added integration test for validation
  - File: `tests/Orders.Tests/Features/CreateOrderTests.cs`
  - Tests: InvalidCustomerId_Returns400, EmptyItems_Returns400
- [x] Fixed N+1 query in GetOrderDetails
  - File: `src/Orders/Features/GetOrderDetails.cs` (line 28)
  - Added `.Include(o => o.Items)` to the query

## Pending
- [ ] Add validation to UpdateOrder command (same pattern as CreateOrder)
  - Start from: `src/Orders/Features/UpdateOrder.cs`
  - Reference: CreateOrder validator for the established pattern
- [ ] Run full test suite — last run had 2 unrelated failures in Catalog module
  - Failures: `CatalogTests.GetProduct_NotFound` and `CatalogTests.ListProducts_Pagination`
  - These appear pre-existing, not caused by today's changes

## Learned
- FluentValidation validators must be registered in the module's DI setup
  (added to `OrdersModule.cs` line 12) — easy to forget
- The N+1 in GetOrderDetails was not caught by existing tests because the test
  fixture seeds only 1 item per order. Consider adding multi-item test data.

## Context
- Working in the `feature/order-validation` branch
- All changes committed up to "Add CreateOrder validation + tests"
- No uncommitted changes

Trigger Detection

Recognize when the user is ending a session:

EXPLICIT SIGNALS:
- "Let's wrap up"
- "That's all for today"
- "I'm done"
- "Save progress"
- "Let's stop here"
- "End of session"
- "Handoff"
- "Pick this up tomorrow"

IMPLICIT SIGNALS:
- User says "thanks" after a series of completed tasks
- User says "good enough for now"
- Long pause after completing a task followed by no new request

RESPONSE:
When you detect a wrap-up signal, offer to write the handoff:
"Let me write a handoff note to .claude/handoff.md so the next session
can pick up exactly where we left off."

Learning Extraction at Session End

Before writing the handoff, review the session for learnings:

LEARNING EXTRACTION CHECKLIST:
1. Did the user correct anything? → Capture in MEMORY.md (via self-correction-loop)
2. Did we discover something non-obvious? → Add to "Learned" section
3. Did we make a decision with rationale? → Document the "why" in handoff
4. Did a tool/approach not work? → Note it so the next session doesn't retry
5. Did we find a pattern worth reusing? → Note for potential skill/memory addition

EXAMPLES OF GOOD LEARNINGS:
- "EF Core compiled queries don't work with Include() — use regular queries"
- "The payment gateway sandbox returns 500 on amounts > $10,000"
- "FluentValidation async validators need .MustAsync(), not .Must() with await"

EXAMPLES OF BAD LEARNINGS:
- "We worked on the Orders module" (too vague)
- "Things went well" (not actionable)
- "Used TimeProvider" (already a known rule, not a learning)

Anti-patterns

Abrupt Endings

// BAD — session ends with no capture
User: "Thanks, that's all!"
Claude: "You're welcome! Happy to help."
*Next session: "What were we working on? Let me read through the git log..."*

// GOOD — session ends with a handoff
User: "Thanks, that's all!"
Claude: "Before we wrap up, let me write a handoff note to .claude/handoff.md
         so the next session can pick up where we left off."
*Next session: reads handoff, immediately knows the state*

Vague Handoffs

// BAD — handoff that doesn't help
## Completed
- Worked on Orders module

## Pending
- More work on Orders

// GOOD — specific, actionable handoff
## Completed
- [x] Added CreateOrder validation (src/Orders/Features/CreateOrder.cs:15-35)
- [x] Integration test for validation (tests/Orders.Tests/Features/CreateOrderTests.cs)

## Pending
- [ ] Add same validation pattern to UpdateOrder (src/Orders/Features/UpdateOrder.cs)
  - Reference CreateOrder validator for the pattern

Accumulating Handoff Files

// BAD — creating timestamped handoff files
.claude/
├── handoff-2025-07-13.md
├── handoff-2025-07-14.md
├── handoff-2025-07-15.md
*3 files, unclear which is current, stale data accumulating*

// GOOD — single file, always overwritten
.claude/
├── handoff.md    ← always the current state
*Permanent learnings go to MEMORY.md, not handoff files*

Skipping the Learning Extraction

// BAD — handoff without learnings
## Completed
- Fixed N+1 query
## Pending
- Nothing

*The discovery that seeded test data only has 1 item per order (hiding N+1s)
 is lost forever*

// GOOD — extract and preserve the insight
## Learned
- Test fixture seeds only 1 item per order, which hides N+1 queries.
  Consider adding multi-item test data to the default fixture.
→ Also added to MEMORY.md > Testing: "Seed test data with multiple
  child entities to catch N+1 queries"

Decision Guide

ScenarioAction
User says "wrap up" / "that's all" / "done"Write handoff to .claude/handoff.md
Session completed multiple tasksList each with file paths and line numbers
Session had user correctionsExtract to MEMORY.md AND note in handoff Learned section
Next session is likely a different personInclude Decisions Made table with rationale
Session had no pending workStill write a handoff — document what was completed and learned
Previous handoff existsOverwrite it — only the current state matters
Work was on a feature branchInclude branch name and last commit message in handoff
Session ended with failing testsDocument which tests fail and suspected cause in Pending
User doesn't want a handoffRespect it — but suggest capturing learnings in MEMORY.md at minimum
Session was purely exploratory (no code changes)Write a lighter handoff with findings and recommendations

平台分布

Codex

34.56%
按下载量换算57

Claude

33.14%
按下载量换算55

Cursor

20.45%
按下载量换算34

Gemini CLI

9.22%
按下载量换算15

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。目前只有一个公开来源,建议同时核对源仓库。

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