LLMOps · Eval

Because editing a dozen config files just to try a new model is a waste of keystrokes.

A ruleset that treats every line of generated code as an admission of defeat.

Impeccable exists to stop AI coding assistants from defaulting to the same handful of SaaS-template tells—Inter everywhere, nested cards, purple gradients—by giving them a curated design vocabulary and 27 deterministic anti-pattern rules.

iFixAi runs up to 32 inspections against any LLM or agent and returns a letter-grade scorecard in minutes, using a separate provider as judge so the model isn't grading its own homework.

RocketRide exists because wiring LLM workflows shouldn't require leaving your IDE or surrendering your data to a cloud dashboard.

Hallmark is a design skill that stops Claude, Cursor, and Codex from producing the same generic AI slop.

A Rust-based runtime that sandboxes autonomous agents with declarative YAML policies and hot-reloadable network controls.

Paperclip exists because twenty Claude Code tabs and a folder of bash scripts do not constitute a company.

This curriculum closes the gap between calling AI APIs and understanding the loss curves underneath.

Open-source role templates that teach Claude your team's tools, terminology, and workflows so you stop repeating yourself.

Juggling Claude Code, Codex, Gemini CLI, and friends from separate terminals gets old fast.

Ruflo turns Claude Code from a solo assistant into a coordinated swarm with shared memory, plugins, and cross-machine federation.

It strips the telltale signs of AI-generated writing from text, replacing statistical blandness with prose that sounds like it came from a person.

It turns a single keyword into a finished HD short video by automating scriptwriting, stock-footage sourcing, voice synthesis, subtitling, and final render.

Hermes exists so you can stop re-teaching assistants that are supposed to remember, and run them on a $5 VPS instead of your laptop.

Hypit gives AI agents a markup language and compiler to turn reference clips—or text prompts—into templated, batch-rendered video variants.

Headroom sits between your agents and the LLM to compress tool outputs, logs, and RAG chunks, delivering the same answers with a fraction of the tokens.

An AI job-search filter that scores listings, tailors your CV per role, and tracks the pipeline so you only apply to jobs worth keeping.

Because verbose AI explanations waste tokens and patience, this skill makes agents talk like cavemen—terse, accurate, and cheap.

Context Mode is an MCP server that sandboxes bloated tool output and persists session memory in SQLite so AI agents don't lose their place when the context window compacts.