How do I install the Checkpoint skill?

Run npx skillmds@latest add aiskillstore/checkpoint-2 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Checkpoint skill do?

Save current progress to memory-keeper to prevent work loss. It is listed under Coding & Dev Tools on SkillMD.

Is Checkpoint safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Checkpoint?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Checkpoint free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Checkpoint?

aiskillstore (@aiskillstore) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Checkpoint by aiskillstore — Agent Skill

Name: Checkpoint
Rating: 4.2 (5 reviews)
Author: aiskillstore

File contents

Checkpoint Skill

Automatically checkpoint current progress to memory-keeper to prevent catastrophic work loss when context is exhausted.

When to Use

Every 5-10 tool calls during implementation
After completing a significant piece of work
Before starting a large operation
When switching tasks
Before ending a session
When explicitly requested via /checkpoint

Checkpoint Actions

1. Gather Current State

Collect the following information:

Current task description from todo list
List of files modified this session
Implementation progress (percentage or phase)
Current blockers or issues
Next action to take

2. Save to Memory-Keeper

context_save(key: "current-task", value: "<task description>", category: "progress", priority: "high")
context_save(key: "files-modified", value: "<comma-separated file list>", category: "progress")
context_save(key: "implementation-progress", value: "<percentage or phase>", category: "progress")
context_save(key: "next-action", value: "<exact next step>", category: "progress", priority: "high")

3. Create Named Checkpoint

context_checkpoint(
  name: "checkpoint-<timestamp>",
  description: "Task: <task>, Progress: <progress>, Files: <count>, Next: <action>"
)

4. Prepare for Compaction (if context is large)

context_prepare_compaction()

Checkpoint Frequency Guidelines

Activity	Checkpoint Frequency
File creation/modification	After every file
Running tests	After each test run
Research/exploration	Every 10 tool calls
Debugging	After each hypothesis tested
Multi-step implementation	After each step

Key Items to Always Save

Key	Description	Priority
`current-task`	What you're currently working on	high
`files-modified`	All files touched this session	normal
`implementation-progress`	How far along (%, phase)	normal
`next-action`	Exact next step to take	high
`blockers`	Current issues/blockers	high
`todo-state`	Serialized todo list	normal

Checkpoint Output

After checkpointing, confirm with:

Checkpoint saved:
- Task: <current task>
- Progress: <progress>
- Files modified: <count>
- Next action: <next step>

Recovery Reference

If context is lost, use /recover to restore state from checkpoints.

--- name: checkpoint-2 description: Save current progress to memory-keeper to prevent work loss. --- # Checkpoint Skill Automatically checkpoint current progress to memory-keeper to prevent catastrophic work loss when context is exhausted. ## When to Use - Every 5-10 tool calls during implementation - After completing a significant piece of work - Before starting a large operation - When switching tasks - Before ending a session - When explicitly requested via `/checkpoint` ## Checkpoint Actions ### 1. Gather Current State Collect the following information: - Current task description from todo list - List of files modified this session - Implementation progress (percentage or phase) - Current blockers or issues - Next action to take ### 2. Save to Memory-Keeper ``` context_save(key: "current-task", value: "<task description>", category: "progress", priority: "high") context_save(key: "files-modified", value: "<comma-separated file list>", category: "progress") context_save(key: "implementation-progress", value: "<percentage or phase>", category: "progress") context_save(key: "next-action", value: "<exact next step>", category: "progress", priority: "high") ``` ### 3. Create Named Checkpoint ``` context_checkpoint( name: "checkpoint-<timestamp>", description: "Task: <task>, Progress: <progress>, Files: <count>, Next: <action>" ) ``` ### 4. Prepare for Compaction (if context is large) ``` context_prepare_compaction() ``` ## Checkpoint Frequency Guidelines | Activity | Checkpoint Frequency | |----------|---------------------| | File creation/modification | After every file | | Running tests | After each test run | | Research/exploration | Every 10 tool calls | | Debugging | After each hypothesis tested | | Multi-step implementation | After each step | ## Key Items to Always Save | Key | Description | Priority | |-----|-------------|----------| | `current-task` | What you're currently working on | high | | `files-modified` | All files touched this session | normal | | `implementation-progress` | How far along (%, phase) | normal | | `next-action` | Exact next step to take | high | | `blockers` | Current issues/blockers | high | | `todo-state` | Serialized todo list | normal | ## Checkpoint Output After checkpointing, confirm with: ``` Checkpoint saved: - Task: <current task> - Progress: <progress> - Files modified: <count> - Next action: <next step> ``` ## Recovery Reference If context is lost, use `/recover` to restore state from checkpoints.

Frequently asked questions

Checkpoint