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checkpointcheckpoint 搜索

Agent Skill

checkpoint 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

569

周安装

23

GitHub Stars

4

下载量

178
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

2

许可证

unknown

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:checkpoint(checkpoint 搜索)
来源仓库:https://github.com/petekp/agent-skills
仓库路径:skills/checkpoint
安装命令:
npx skills add https://github.com/petekp/agent-skills --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/petekp/agent-skills --skill checkpoint

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合围绕仓库状态、代码变更或协作事项进行整理。
  • 可结合来源仓库和原始 README 继续核验具体用法。
  • 安装前建议确认权限范围、维护状态及是否会触发联网或命令执行。
  • 当前归类为开发,功能描述一致,使用方式明确。checkpoint 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Checkpoint

Pause, assess, and surface intelligent next-step options to the user.

When to Trigger Proactively

Suggest this skill (without being asked) when detecting:

  • Completion signal: A feature, fix, or milestone just finished
  • Uncertainty signal: Requirements unclear, multiple valid paths, or low confidence in current direction
  • Complexity signal: Scope expanded, unexpected dependencies emerged, or task is taking longer than expected
  • Drift signal: Work may have diverged from user's original intent
  • Quality signal: Code works but may benefit from review, testing, or refactoring

Workflow

1. Context Assessment

Silently evaluate the current state across these dimensions (do not output this analysis):

  • Progress: What has been accomplished? What remains?
  • Quality: Is the work solid, or are there rough edges?
  • Alignment: Does recent work match what the user actually wants?
  • Uncertainty: What assumptions were made? What's unclear?
  • Risk: What could go wrong? What hasn't been tested?
  • Efficiency: Is there a better path forward?

2. Generate Options

Based on assessment, generate 2-5 contextually-appropriate options. Draw from (but don't limit to) these archetypes:

ArchetypeWhen Relevant
Commit progressMeaningful progress made, good stopping point
Systems auditComplex changes, potential for bugs or regressions
Prioritize/planMultiple pending tasks, unclear what matters most
Re-evaluate decisionsLow confidence in recent choices, new information available
Clarify with userAssumptions made, requirements ambiguous
Test/verifyCode works but edge cases untested
Refactor/clean upCode functional but messy
DocumentComplex logic that needs explanation
Step backMay be overcomplicating or missing simpler solution
Continue current pathClear next step, no reason to pause

Option generation principles:

  • Options should be meaningfully different, not variations of the same thing
  • Include at least one "continue forward" option when momentum is valuable
  • Include at least one "pause and verify" option when risk is present
  • Avoid analysis paralysis - fewer sharp options beat many vague ones

3. Select Recommendation

Choose one option as recommended. The recommendation should reflect:

  • What would a thoughtful senior engineer do here?
  • What reduces risk of wasted effort or rework?
  • What serves the user's underlying goals (not just stated requests)?

4. Present via AskUserQuestion

Use AskUserQuestion with this structure:

Question: "What would you like to do next?"
Header: "Next step" (or contextually appropriate 1-2 words)
Options: [generated options with descriptions]

Option format:

  • label: Action verb phrase (e.g., "Commit current progress", "Run systems audit")
  • description: 1 sentence explaining what this involves and why it might be valuable

Recommendation:

  • Place recommended option FIRST in the list
  • Append "(Recommended)" to its label
  • Include rationale in the description

Example Output

For a scenario where a feature was just implemented but with some shortcuts:

AskUserQuestion:
  question: "Feature implementation complete. What would you like to do next?"
  header: "Next step"
  options:
    - label: "Review and refactor (Recommended)"
      description: "Clean up the shortcuts taken during implementation before they become technical debt. The core logic works but could be more maintainable."
    - label: "Add test coverage"
      description: "Write tests for the new feature to catch edge cases and prevent regressions."
    - label: "Commit and move on"
      description: "The feature works - commit it and tackle the next task. Can refactor later if needed."
    - label: "Walk me through what was built"
      description: "Explain the implementation so you can verify it matches your expectations before proceeding."

Anti-Patterns

  • Don't overthink: This skill should take seconds, not minutes
  • Don't list every possible option: Curate the most valuable 2-5
  • Don't recommend "ask user" when the situation is clear: Have a point of view
  • Don't trigger too frequently: Reserve for genuine decision points, not every minor step
  • Don't explain the assessment process: Just present the options naturally

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

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

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

Codex

36.62%
按下载量换算65

Claude

30%
按下载量换算53

Cursor

17.83%
按下载量换算32

Gemini CLI

7.83%
按下载量换算14

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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