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Agent Skill · 研究检索

checkpoint(checkpoint 搜索)

checkpoint 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。

checkpoint 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,权限为需要联网;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 43,402。

总安装 988周安装 42GitHub Stars 6下载 346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:checkpoint(checkpoint 搜索)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/checkpoint
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill checkpoint
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/duc01226/easyplatform --skill checkpoint

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。

checkpoint 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景进行信息检索和来源线索筛选的场景。通过 npx skills add 命令从指定 GitHub 仓库安装使用。

安装前需确认权限范围、维护状态及是否触发联网或文件操作。checkpoint 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/checkpoint

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/duc01226/easyplatform --skill checkpoint;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

checkpoint 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill checkpoint。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

checkpoint 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。

checkpoint 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。

checkpoint 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。

checkpoint 用的人多吗?

公开数据是累计安装 988 次,近一周安装 42 次,下载 346 次,GitHub 6 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。

checkpoint 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。

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。

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
checkpoint

checkpoint 搜索 · 本页

9886需要联网未明确通过

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

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
AI Mistake Prevention — Failure modes to avoid on every task: - Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. - Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. - Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. - Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. - When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. - Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. - Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. - Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. - Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. - Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Quick Summary

Goal: Save current analysis context and progress to an external file for recovery after context loss.

Workflow:

  1. Gather Context — Collect task state, findings, files analyzed, decisions made
  2. Write Checkpoint — Save structured markdown to plans/reports/checkpoint-{timestamp}-{slug}.md
  3. Update Todos — Reflect checkpoint creation in task tracking

Key Rules:

  • Save checkpoints every 30-60 minutes during complex tasks
  • Include file paths, line numbers, and recovery instructions
  • Document decisions with rationale for future reference

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Save Memory Checkpoint

Save current analysis, findings, and progress to an external memory file to prevent context loss during long-running tasks.

Usage

Use this command when:

  • Working on complex multi-step tasks (investigation, planning, implementation)
  • Before expected context compaction
  • At key milestones during feature development
  • After completing significant analysis phases

Checkpoint File Location

Files are saved to: plans/reports/checkpoint-{timestamp}-{slug}.md

Instructions

Create a checkpoint file with the following structure:

Step 1: Determine Checkpoint Location

# Get current date for filename
date +%y%m%d-%H%M

Step 2: Gather Context

Collect and document:

  1. Current Task - What are you working on?
  2. Key Findings - What have you discovered?
  3. Files Analyzed - Which files have been read/modified?
  4. Progress Summary - What's completed vs remaining?
  5. Important Context - Critical information to preserve
  6. Next Steps - What should be done next?
  7. Open Questions - Unresolved issues

Step 3: Write Checkpoint File

Create a markdown file at plans/reports/checkpoint-YYMMDD-HHMM-{task-slug}.md with:

# Memory Checkpoint: [Task Description]

> Checkpoint created to preserve analysis context during [task type].

## Session Info

- **Created:** [timestamp]
- **Task:** [description]
- **Branch:** [git branch]
- **Phase:** [current phase]

## Current Task Summary

[Brief description of what you're working on]

## Key Findings

### Analysis Results

- [Finding 1]
- [Finding 2]
- [Finding N]

### Patterns Discovered

- [Pattern 1]
- [Pattern 2]

### Dependencies Identified

- [Dependency 1]
- [Dependency 2]

## Files Context

### Analyzed Files

| File            | Purpose   | Relevance       |
| --------------- | --------- | --------------- |
| path/to/file.cs | [purpose] | High/Medium/Low |

### Modified Files

- `path/to/modified.ts` - [change description]

### Pending Files

- `path/to/pending.cs` - [why pending]

## Progress Summary

### Completed

- [x] [Completed item 1]
- [x] [Completed item 2]

### In Progress

- [ ] [Current item]

### Remaining

- [ ] [Remaining item 1]
- [ ] [Remaining item 2]

## Important Context

### Critical Information

[Information that must not be lost]

### Assumptions Made

- [Assumption 1]
- [Assumption 2]

### Decisions Made

- [Decision 1] - [rationale]
- [Decision 2] - [rationale]

## Next Steps

1. [Immediate next action]
2. [Following action]
3. [Subsequent action]

## Open Questions

- [ ] [Question 1]
- [ ] [Question 2]

## Recovery Instructions

To resume this task after context reset:

1. Read this checkpoint file
2. Review [specific files] for context
3. Continue from [specific point]

---

_Checkpoint saved by Claude Code at [timestamp]_

Step 4: Update Todo List

Update your todo list to reflect checkpoint was created:

- [x] Create memory checkpoint at [timestamp]

Best Practices

  1. Save checkpoints frequently - Every 30-60 minutes during complex tasks
  2. Be specific - Include file paths, line numbers, exact findings
  3. Document decisions - Record why choices were made
  4. Link related files - Reference other analysis documents
  5. Include recovery steps - Make resumption easy

Related Commands

  • /context - Load project context
  • /compact - Manually trigger context compaction
  • /watzup - Generate progress summary

Closing Reminders

  • MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

平台分布

Codex

35.53%
按下载量换算123

Claude

28.2%
按下载量换算98

Cursor

18.35%
按下载量换算63

Gemini CLI

9.96%
按下载量换算34

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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