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Checkpoint Guardian

Checked
fatih-developer·vlatest·other·MIT

The Checkpoint Guardian skill monitors and alerts you to potential security breaches or unauthorized access attempts at your checkpoints, ensuring data integrity.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add fatih-developer/fth-skills --skill checkpoint-guardian -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

fatih-developer

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned fatih-developer/fth-skills at f0d82e9b4f.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
f0d82e9b4f
Manifest
skills/checkpoint-guardian/SKILL.md
Scanned
5 files, 325 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The checkpoint-guardian skill provides a mechanism for AI agents to periodically verify and restore their state. It allows an agent to save its current progress, then later reload that saved state if needed, ensuring resilience against interruptions or errors. This is particularly useful for long-running tasks where data loss would be detrimental.

When to use it

  • Long processes: Use when the AI agent is performing a task that takes a significant amount of time (e.g., generating a large document).
  • Unreliable environments: Employ in situations where the environment might experience interruptions or instability, requiring state recovery.
  • Complex workflows: Integrate into multi-step workflows to safeguard progress at key decision points.
  • Data-intensive tasks: When dealing with significant data manipulation, checkpointing prevents loss of work due to unexpected failures.

Key capabilities

  • State saving (checkpointing)
  • State restoration from checkpoints
  • Periodic checkpoint creation

Example prompts

  • "Create a checkpoint and save my current progress."
  • "Restore the agent's state from the last saved checkpoint."
  • “Save a checkpoint every 5 minutes.”

Tips & gotchas

The frequency of checkpointing should be balanced against performance overhead. More frequent checkpoints consume more resources but offer finer-grained recovery; less frequent checkpoints are lighter but may result in larger data loss upon failure.