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Speed Of Light

Listed
simhacker·vlatest·other·MIT

This skill instantly completes a single action, dramatically accelerating tasks and offering tactical advantages in fast-paced situations.

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 simhacker/moollm --skill speed-of-light -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

simhacker

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 simhacker/moollm at 8f6d840b2f.

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

Scanned
0 files
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 speed-of-light skill allows AI agents to process information and respond at an accelerated rate. It optimizes internal workflows, reducing latency in tasks like data retrieval, analysis, and text generation. This results in faster response times and improved overall agent efficiency.

When to use it

  • Rapid prototyping: Quickly iterate on ideas by minimizing the time spent waiting for AI responses during development.
  • Real-time applications: Improve responsiveness in scenarios requiring immediate feedback, such as live chat or interactive games.
  • High-volume task processing: Accelerate the completion of large datasets or numerous requests where speed is critical.
  • Complex reasoning chains: Reduce the overall time required for agents to execute multi-step decision-making processes.

Key capabilities

  • Optimized internal workflows
  • Reduced latency in data retrieval
  • Accelerated text generation
  • Improved agent efficiency

Example prompts

  • "Analyze this document and summarize it quickly."
  • "Generate five different marketing slogans as fast as possible."
  • "Translate this paragraph into Spanish, prioritizing speed over perfect accuracy."

Tips & gotchas

The skill’s effectiveness depends on the underlying AI model's capabilities. While speed-of-light optimizes processing, it cannot fundamentally alter the limitations of the base model itself.