lowfat - slim your command output. strips noise, saves tokens.

Simple random DNS, HTTP/S internet traffic noise generator

A Chrome/Firefox extension with custom new tab page featuring Chinese poems and P5.js enabled noise waves in traditional Chinese colors

Golang CLI application development. Use when building, modifying, or reviewing a Go CLI tool — especially for command structure, flag handling, configuration layering, version embedding, exit codes, I/O patterns, signal handling, shell completion, argument validation, and CLI unit testing. Also triggers when code uses cobra, viper, or urfave/cli. For cobra-specific APIs → See `samber/cc-skills-golang@golang-spf13-cobra` skill; for viper configuration layering → See `samber/cc-skills-golang@golang-spf13-viper` skill.

Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while `samber/cc-skills-golang@golang-performance` provides the optimization patterns.

An open-source model for calculating noise maps.

A Claude skill for structured financial market intelligence using first principles and system thinking.

Claude Code skill for capturing and codifying learnings before session ends / context lost

The context intelligence layer for AI coding agents. Compressing noise, routing content to the right strategy, preserving session state across compactions, and surfacing the files that actually matter.

Flowing from Vision to Action: Noise-Free Flow Matching Policy Learning 🎉[ICLR 2026]

A token-saving plugin for AI coding agents that reduces output narration and log verbosity to cut token costs.

The highfrequency package contains an extensive toolkit for the use of highfrequency financial data in R. It contains functionality to manage, clean and match highfrequency trades and quotes data. Furthermore, it enables users to: calculate easily various liquidity measures, estimate and forecast volatility, and investigate microstructure noise and intraday periodicity.