larsboes

Swift code quality rules for mach-mono — 300-line file limit, @Observable, no singletons in views, no direct Defaults access, protocol-based services. Auto-loaded when editing .swift files.

mach-mono visual design rules — minimalistic aesthetic, clarity, cohesion, tech-forward style, iconography. Auto-loaded when working on UI/view files.

mach-mono git branching, integration, and release workflow — main as canonical branch, topic branches, commit shape, deploy via tags.

machNotch plugin architecture rules — NotchPlugin protocol, lifecycle, DI via PluginContext, HUD event bus, PluginSettings. Auto-loaded when working in Plugins/.

mach-mono refactoring rules — file-by-file approach, dependency tier order, extract-don't-delete, build after each file, commit granularity.

Save session context before ending a conversation. Updates CLAUDE.md with learnings and creates a session summary for resuming work later.

Expert guidance on Swift Concurrency best practices, patterns, and implementation. Use when developers mention: (1) Swift Concurrency, async/await, actors, or tasks, (2) "use Swift Concurrency" or "modern concurrency patterns", (3) migrating to Swift 6, (4) data races or thread safety issues, (5) refactoring closures to async/await, (6) @MainActor, Sendable, or actor isolation, (7) concurrent code architecture or performance optimization, (8) concurrency-related linter warnings (SwiftLint or similar; e.g. async_without_await, Sendable/actor isolation/MainActor lint).

Use when working with Swift code, especially macOS SwiftUI apps with modern concurrency, plugin architectures, and dependency injection. Covers @MainActor, @Observable, structured concurrency, protocol-based design, and Swift 6 migration.

Drafts, critiques, and cite-checks academic writing (thesis chapters, conference/journal papers) across two genre profiles — empirical-CS/paper and DSR/qualitative-thesis — with a genuinely adversarial multi-skeptic critique pass and Quarto/BibTeX-aware citation tooling. Use when drafting a section from bullet points, running a flow/reverse-outline check on a draft, running a hard-critic or red-team review pass on a chapter or paper, or validating/resolving citations and checking citation-key coverage. Do not use for README/user docs, general non-academic prose, or as a ghostwriter — it produces sourced skeletons and critique, not net-new prose, unless the calling context explicitly grants an exception.

Builds a job-tailored CV PDF from a single profile-tagged master CV file, via the local `cv` CLI — pick the closest profile tag (or ask), pick a language, run the build, hand back the PDF path. Use when the user wants a CV/resume for a specific job application, role type, or language. Do not use for writing or editing CV content itself (that's the master file, edited by hand) or for any content-generation/AI-tailoring flow — this skill only filters and renders what's already in the master file.

Strips the tells that make source code read as AI-generated and forces code that fits the project instead of the model's default average. It does not write the code, and it has no preferred style. It removes the surface tells (leftover chat artifacts, placeholder comments, emoji, swallowed errors, narrating comments, generic placeholder names like process_data) AND surfaces the structural tells a linter passes: boilerplate / tutorial-shaped code, hallucinated APIs, over-engineering, and code that ignores the surrounding codebase. Grounded in a Reddit analysis of 11,906 posts and 11,306 comments across 55 AI, coding, and SaaS subreddits of what developers actually name as a giveaway. Use whenever writing, generating, reviewing, refactoring, or auditing code, and especially when the user wants it to not look AI-written or vibe-coded, says it "looks AI-generated," "reads like a tutorial," "is too generic," or "de-slop this." Trigger even if they never say "AI tell."

Strips the cues that make prose read as AI-generated and forces a deliberate human voice instead of the model's default register. It has no house style and does not draft prose. It removes the cited tells (the em dash, the "it's not just X, it's Y" cadence, assistant boilerplate, the delve/tapestry diction, listicle scaffolding, the "in conclusion" wrap-up) and warns against the over-corrected "trying not to sound like AI" register that swaps one default for another. Grounded in a Reddit analysis of 89,239 posts (7,984 on-topic) across roughly 50 AI, writing, and SaaS subreddits of what people name as a giveaway. Use when writing, drafting, editing, rewriting, reviewing, or auditing any prose for a reader (a post, email, essay, README, or marketing copy), and especially when the user wants it to sound human rather than AI, or says it "sounds like ChatGPT," "reads like AI," "is too polished," "de-slop this," or "make it sound like me." Trigger even if they never say "AI tell."

Strips the cues that make a website read as AI-generated and forces a deliberate, project-specific design choice instead of the model's default. It does not impose a look or hand out taste. It removes tells (default shadcn/Tailwind, AI-purple gradients, gradient heading text, unprompted neon glow, emoji-as-icons, the centered hero plus three feature cards) AND the newer cream-plus-serif-plus-sage "tasteful default" that trading one default for another creates. Grounded in a 47-subreddit, 3.2M-post Reddit analysis of what people flag as AI slop. Use whenever building, styling, reviewing, refactoring, or auditing any website, landing page, web app UI, dashboard, or front-end component, especially when the user wants a site to look custom or human rather than AI-generated, or mentions AI slop, looks AI-made, generic, vibe-coded, Tailwind, or shadcn. Trigger even if they never say vibe-coded.

Authors, structures, and audits Claude agent skills (SKILL.md + scripts/references/assets) to Anthropic best-practices, the agentskills.io spec, and local Claude Code conventions. Use when creating a new skill, refactoring one for progressive disclosure, or auditing a skill's metadata/structure. Do not use for README/user docs, non-agentic library code, or MCP-server implementation — for a runbook-style domain skill, model it on a sibling under `.claude/skills/`.

Slices models and drives a home Klipper/Moonraker 3D printer via the local printctl CLI — slice with OrcaSlicer, upload, arm, start, monitor, pause/cancel, e-stop — with hard temperature caps and an arm-before-heat gate. Works with any Klipper/Moonraker printer; the specific model, material and caps come from config (run `printctl doctor`). Use when the user wants to 3D-print at home, slice an STL/3MF, or check/control the printer. Do not use for CAD/mesh modeling, cloud/non-local printers, or non-Klipper firmware.

Builds and maintains a persistent, LLM-maintained wiki inside an Obsidian vault — the LLM writes/maintains all pages, the human curates sources and asks questions. Ingest a source, query across pages, or lint for stale/contradictory/orphan content. Vault root comes from the overlay (config/knowledge.toml). Use when ingesting an article/paper/transcript into the vault, synthesizing across notes, health-checking the wiki, or building a knowledge structure for a domain. Do not use for code documentation, one-off notes, or non-vault knowledge.

Use when writing or editing FluentBit configs (YAML/conf), Lua filters for FluentBit, FluentBit CI pipelines, or testing Lua filters with FluentBit. Also use when debugging FluentBit Lua filter behavior, return codes, or field mapping issues.