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Claude Skills by petekp
github.com/petekp69 skills4 installs176 views
- Literate GuideCreate a narrative guide to a codebase or feature in the style of Knuth's Literate Programming — code and prose interwoven as a single essay, ordered for human understanding rather than compiler needs. Use when the user asks to 'explain this codebase as a story', 'write a literate guide', 'create a narrative walkthrough', 'tell the story of this code', 'Knuth-style documentation', 'weave a guide for this feature', or when they want deep, readable documentation that treats the program as liter...Votes: 0GitHub stars: 8
- Macos App DesignUse when designing or building native macOS applications with SwiftUI or AppKit. Triggers on menu bar structure, keyboard shortcuts, multi-window behavior, Liquid Glass design system, macOS Tahoe/Sequoia, sidebar navigation, toolbar design, app icons, SF Symbols, or making an app feel like a "good Mac citizen."Votes: 0GitHub stars: 8
- Manual TestingGuide users step-by-step through manually testing whatever is currently being worked on. Use when asked to "test this", "verify it works", "let's test", "manual testing", "QA this", "check if it works", or after implementing a feature that needs verification before proceeding.Votes: 0GitHub stars: 8
- Model First ReasoningApply Model-First Reasoning (MFR) to code generation tasks. Use when the user requests "model-first", "MFR", "formal modeling before coding", "model then implement", or when tasks involve complex logic, state machines, constraint systems, or any implementation requiring formal correctness guarantees. Enforces strict separation between modeling and implementation phases.Votes: 0GitHub stars: 8
- Multi Model Meta AnalysisSynthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than an...Votes: 0GitHub stars: 8
- Optimize Agent DocsBuild a retrieval-optimized knowledge layer over agent documentation in dotfiles (.claude, .codex, .cursor, .aider). Use when asked to "optimize docs", "improve agent knowledge", "make docs more efficient", or when documentation has accumulated and retrieval feels inefficient. Generates a manifest mapping task-contexts to knowledge chunks, optimizes information density, and creates compiled artifacts for efficient agent consumption.Votes: 0GitHub stars: 8
- Posthog AnalyticsProduct analytics expert using PostHog MCP. Triggers on requests to understand user behavior, surface insights, create dashboards, analyze funnels, track metrics, set up experiments, or answer questions about product performance. Use when working with PostHog data, discussing analytics strategy, investigating user journeys, retention, conversion, feature adoption, or when asked to help understand what's happening in the product.Votes: 0GitHub stars: 8
- Process HunterCAVEMAN HUNT BAD PROCESS! Me find greedy creature eating fire and rocks. Me bonk them good. Use when tribe say "kill processes", "clean up servers", "save battery", "find resource hogs", "bonk next.js", or "hunt processes". Me bonk known bad creature automatic. Me ask before bonk mystery creature.Votes: 0GitHub stars: 8
- Proposal ReviewFacilitate methodical review of proposals (technical designs, product specs, feature requests). Use when asked to "review this proposal", "give feedback on this doc", "help me review this RFC", or when presented with a document that needs structured feedback. Handles markdown files, GitHub gists/issues/PRs, and other text formats. Chunks proposals intelligently, predicts reviewer reactions, and produces feedback adapted to the proposal's format.Votes: 0GitHub stars: 8
- Record TodosEnter todo recording mode to capture ideas without acting on them. Use when the user says "record todos", "let's capture some todos", "brainstorm mode", or wants to dump ideas without immediate execution. Captures thoughts to .claude/todos/, then organizes and prioritizes on exit.Votes: 0GitHub stars: 8
- Research PromptCraft a high-quality prompt for a deep research agent (like ChatGPT Deep Research) through adaptive interviewing. Use when the user wants to research something but needs help formulating what to ask — when they say "I need to research X", "help me figure out what to ask about Y", "write a research prompt for Z", "I want to use deep research on...", or when they have a vague research need and want a precise, comprehensive prompt that will get excellent results from a research agent. Also use w...Votes: 0GitHub stars: 8
- Review PackageCreate a self-contained review package of current work for external review by another AI model or human reviewer. Bundles relevant files with a contextual README and instructional prompt. Triggers: "review package", "create review package", "hand off for review", "get a second opinion", "external code review", "cross-model review", "package for review", "prepare code review". Accepts an optional focus area argument to scope the analysis.Votes: 0GitHub stars: 8
- RustRobust Rust patterns for file-backed data, parsing, persistence, FFI boundaries, and system integration. Use when writing Rust that handles file formats, subprocess integration, PID/process management, Serde serialization, or UniFFI boundaries. Covers UTF-8 safety, atomic writes, state machines, and defensive error handling.Votes: 0GitHub stars: 8
- Seam RipperRuthlessly analyze architectural seams—the interfaces, boundaries, and contracts between system components—to expose coupling problems, abstraction leaks, and design failures. Use when asked to review architecture, analyze coupling, find interface problems, improve module boundaries, audit dependencies, or redesign system structure. Produces uncompromising redesign proposals that prioritize correctness over backwards compatibility.Votes: 0GitHub stars: 8
- Simplicity AuditFirst-principles simplification analysis for codebases. Methodically inventories what a codebase actually does, then asks whether each piece of complexity earns its keep. Use when asked to "simplify this codebase", "is this overengineered", "how could this be simpler", "reduce complexity", "first principles review", "essential complexity audit", "do we really need all this", or any request to rethink whether the current implementation is the simplest way to achieve its goals. Also useful when...Votes: 0GitHub stars: 8
- Tuning PanelCreate visual parameter tuning panels for iterative adjustment of animations, layouts, colors, typography, physics, or any numeric/visual values. Use when the user asks to "create a tuning panel", "add parameter controls", "build a debug panel", "tweak parameters visually", "fine-tune values", "dial in the settings", or "adjust parameters interactively". Also triggers on mentions of "leva", "dat.GUI", or "tweakpane".Votes: 0GitHub stars: 8
- TypographyApply professional typography principles to create readable, hierarchical, and aesthetically refined interfaces. Use when setting type scales, choosing fonts, adjusting spacing, designing text-heavy layouts, implementing dark mode typography, or when asked about readability, font pairing, line height, measure, typographic hierarchy, variable fonts, font loading, or OpenType features.Votes: 0GitHub stars: 8
- Unix Macos EngineerExpert Unix and macOS systems engineer for shell scripting, system administration, command-line tools, launchd, Homebrew, networking, and low-level system tasks. Use when the user asks about Unix commands, shell scripts, macOS system configuration, process management, or troubleshooting system issues.Votes: 0GitHub stars: 8
- Write GoalCompile a plain-language task into a concise, auditable Codex or Claude Code `/goal`, or explain why a normal prompt fits better. Use when the user asks to draft, formulate, rewrite, tighten, or create a goal for multi-step work that needs a durable objective, transcript-visible proof, constraints, bounded stop conditions, host-aware operation, and risk-based review depth.Votes: 0GitHub stars: 8