Speed Loop
ListedSpeed Loop rapidly repeats sections of text for emphasis or creative effects – ideal for dramatic pacing and stylistic variation.
Install on your platform
Showing Claude Code. One command installs this skill into any of the agents below.
- 1
Run this in your project
terminal$ npx skills add toomingos/open_speed_optimization_loop --skill speed-loop -a claude-code Uses the open-source
skillsCLI and needs Node.js. Add-gto install it for your user instead of this project.
What we know about this skill
Publisher
toomingos
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.
Automated safety checks
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.
No undeclared network calls: failed
Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: open-speed-loop.vercel.app.
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.
Hosts contacted
open-speed-loop.vercel.appundeclaredgithub.comsource hostWhat it found
- open-speed-loop-website/src/app/layout.tsx:37contacts open-speed-loop.vercel.app
metadataBase: new URL("https://open-speed-loop.vercel.app"), - open-speed-loop-website/src/app/robots.ts:10contacts open-speed-loop.vercel.app
sitemap: "https://open-speed-loop.vercel.app/sitemap.xml", - open-speed-loop-website/src/app/sitemap.ts:4contacts open-speed-loop.vercel.app
const baseUrl = "https://open-speed-loop.vercel.app";
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 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 toomingos/open_speed_optimization_loop at 27a73ca9e6.
The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.
- Commit
- 27a73ca9e6
- Manifest
- SKILL.md
- Scanned
- 60 files, 3,315 lines
About this skill
What it does
The speed-loop skill optimizes code for speed through an iterative process. It identifies performance bottlenecks, suggests improvements, and then retests the modified code in a loop until optimal speed is achieved. This allows for automated refinement of algorithms and functions to maximize efficiency.
When to use it
- Slow scripts: Use when you have Python or Javascript scripts that are taking too long to execute.
- Performance-critical applications: Ideal for optimizing sections of code in games, simulations, or data processing pipelines where speed is paramount.
- Algorithm refinement: Helpful for improving the efficiency of custom algorithms and functions.
- Benchmarking: To systematically improve performance metrics over time.
Key capabilities
- Automated performance bottleneck identification
- Code modification suggestions
- Iterative testing and optimization loop
- Support for Python and Javascript code
Example prompts
- "Optimize this Python function for speed: [paste code here]"
- "Can you make this JavaScript script run faster? [paste code here]"
- "Improve the performance of my sorting algorithm."
Tips & gotchas
The skill requires access to both the source code and a testing environment. It's recommended to start with smaller, isolated sections of code for initial optimization runs.