maragudk

Guide for using git with specific preferences -- backticks around code identifiers in commit messages, asking about GitHub issues to reference before committing. Use this whenever you commit, write a commit message, or work with pull requests -- not just when…

Guide for making code reviews. Use this when asked to make code reviews, or ask to use it before committing changes.

Comprehensively reviews SwiftUI code for best practices on modern APIs, maintainability, and performance. Use when reading, writing, or reviewing SwiftUI projects.

Design and build native-feeling macOS application UIs. Use this skill whenever the user asks to create a desktop app, macOS app, Mac-style interface, Apple-style UI, system utility, or anything that should look and feel like a native Mac application. Also…

Always use when creating and editing Swift files (*.swift)

Get a second opinion from another AI model (currently OpenAI models, via the codex CLI) on a design decision, a stubborn bug, a code review, or any question where an independent take is valuable. Use only when the user explicitly asks for one -- "get a second…

Guide for working with XBRL, the standard for digital business and financial reporting -- reading and writing instance documents, Inline XBRL (iXBRL), xBRL-JSON and xBRL-CSV, taxonomies and linkbases, dimensions, contexts, units, and facts. Use this skill…

ALWAYS invoke this skill as your FIRST action — before any Read, Write, Edit, or Bash — whenever a task involves Go in any way — creating or editing any `.go` file, `go.mod`, or `go test`; adding or changing handlers, structs, methods, interfaces, error…

Autonomous project gardening. Scans for maintenance issues (starting with documentation), picks one, fixes it in a worktree, self-reviews with competing agents, and opens a PR. Use when the user wants to tidy up the project, fix stale docs, or generally tend…

Write and maintain an implementation diary capturing what changed, why, what worked, what failed (with exact errors and commands), what was tricky, and how to review and validate. Activates proactively during non-trivial implementation work (new features, bug…

Autonomous experiment loop that iteratively improves a measurable metric. Given a goal, a verify command, and an optional guard, the agent branches, makes one change, measures the result, and keeps or discards the experiment -- repeating indefinitely. Use…

Address code review feedback by walking through comments one at a time with the user. Use when the user has received code review comments — on a GitHub PR, in a document in the repo, or directly in conversation — and wants to work through them methodically.…

Guide for how to develop Go apps and modules/libraries. Always use this skill when reading or writing Go code.

Guide for posting content to the Bluesky social network using the bsky terminal app. This skill should be used proactively when working in public repositories and there is interesting, shareable content (new features, insights, achievements, or announcements…

For when you're asked to write a design doc or specification, especially after a brainstorm or feature design session.

Guide for creating and working with marimo notebooks, the reactive Python notebook that stores as pure .py files. This skill should be used when creating, editing, running, or deploying marimo notebooks.

Generate a custom trace annotation web app for open coding during LLM error analysis. Use when the user wants to review LLM traces, annotate failures with freeform comments, and do first-pass qualitative labeling (open coding). Also use when the user mentions…

Build a structured taxonomy of failure modes from open-coded trace annotations. Use this skill whenever the user has freeform annotations from reviewing LLM traces and wants to cluster them into a coherent, non-overlapping set of binary failure categories…

Use this skill when crafting, reviewing, or improving prompts for LLM pipelines — including task prompts, system prompts, and LLM-as-Judge prompts. Triggers include: requests to write or refine a prompt, diagnose why an LLM produces inconsistent or incorrect…

Build, validate, and deploy LLM-as-Judge evaluators for automated quality assessment of LLM pipeline outputs. Use this skill whenever the user wants to: create an automated evaluator for subjective or nuanced failure modes, write a judge prompt for Pass/Fail…