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Lofi Gate Checkpoint

Checked
lofi-monk·vlatest·other·MIT

This skill checks if a lo-fi stream is consistently gated, ensuring uninterrupted listening and preventing abrupt stops.

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 lofi-monk/lofi-gate --skill lofi-gate-checkpoint -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

lofi-monk

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 lofi-monk/lofi-gate at d9280c6bf9.

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

Commit
d9280c6bf9
Manifest
.agent/skills/lofi-gate-checkpoint/SKILL.md
Scanned
2 files, 251 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 lofi-gate-checkpoint skill provides a mechanism to pause and resume AI agent workflows. It allows you to define checkpoints within a sequence of actions, enabling agents to save their state and later pick up where they left off. This is particularly useful for long or complex tasks that might be interrupted.

When to use it

  • Long-running processes: If your agent performs tasks that take significant time (e.g., data analysis, content generation), checkpoints prevent loss of progress due to interruptions.
  • Complex workflows: Break down intricate procedures into manageable steps with checkpoints for easier debugging and control.
  • Resource constraints: Save the current state when resources are low and resume later when more resources become available.
  • Multi-stage tasks: Implement a workflow that requires multiple stages, allowing the agent to save its progress at each stage before moving on.

Key capabilities

  • Define checkpoints within workflows.
  • Save agent state at defined checkpoints.
  • Resume execution from previously saved checkpoints.
  • Handle interruptions and restarts gracefully.

Example prompts

  • "Create a checkpoint named 'data_analysis_complete' after processing the first 100 records."
  • "Resume the workflow from the 'data_analysis_complete' checkpoint."
  • "Save the current state as checkpoint 'report_draft'."

Tips & gotchas

The skill requires careful planning of checkpoint placement within your agent’s workflow to ensure meaningful and recoverable states. Consider what data needs to be saved at each checkpoint for a successful resumption.