24건(nateslabach의 저장소) · 인기순
Disables the AI's default hedging, diplomatic softening, and social-nicety layers to deliver cold, unfiltered, consequentialist analysis on any topic. Use when the user wants the AI's actual assessment without padding, regardless of how harsh or uncomfortable the honest answer is.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generates complete, production-ready React/TypeScript components using Tailwind CSS. Use when building UI components in a React or Next.js project that requires TypeScript, Tailwind styling, and accessible interactions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Formats output for ADHD-friendly action — lead with the next step, number tasks, restate state, cut fluff. Use when named (adhd), when the user mentions ADHD or focus/executive-function constraints, or when they ask for steps they can execute immediately.
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Stops "just one more" small tweaks that add scope without changing the outcome. Use when named (just-stop), or when about to implement extra polish, cleanup, or drive-by fixes beyond the stated goal.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-review.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Hostile self-review of recently written AI workflow code that then applies fixes (agents, tools, chat context, summarization, tokens, attachments). Use after generating AI systems code, or when asked to self-review and harden it. Not for PR peer review (code-review) or no-edit devil's-advocate attacks (adversarial-challenge). Prefer: adversarial-challenge → decide → this skill.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Produces thorough, multi-source cited research reports from web and news without paid APIs. Use when the user asks for deep research, landscape analysis, competitive intel, market research, or a cited report needing broad source coverage.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Applies Chesterton's Fence, Occam's Razor, the Peter Principle, and Dunning-Kruger to technical decisions. Use before refactoring, architectural changes, or any task where changing existing behavior carries risk or requires judgment about what the user actually needs.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Strips AI fingerprints from written text by enforcing banned vocabulary, forbidden sentence structures, and authentic prose patterns. Use when writing articles, documentation, social content, emails, or any text that should read as human-authored rather than AI-generated.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Ground rules for an effective subagent in a loop, workflow, or graph run. Stay in scope, escalate when stuck, return structured results. Use when acting as a subagent, writing subagent prompts, or reviewing delegated agent behavior.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Applies a modern CSS reset covering box-sizing, margin removal, text rendering, media defaults, and root stacking context. Use when starting a new web project, creating a global stylesheet, or when the codebase lacks sensible CSS defaults.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Writes in ASD-STE100 simplified technical English — short sentences, plain words, active voice. Use when the user wants terse technical prose, names this skill, or asks for STE100.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Builds personal brand assets using Seth Godin's frameworks: signature symbol, slogan, surprise (Purple Cow), salient idea, and signature story. Use when named (branding), or when the user asks for a brand symbol, slogan, tagline, Purple Cow, counterintuitive angle, core idea, brand story, or personal brand positioning.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Structured 3-phase peer review of a diff or PR — intent, issues by severity, then pointed merge-readiness questions and a verdict. Use for general code review. Not for AI workflow self-fix-and-edit (ai-systems-review) or no-edit devil's-advocate threat models (adversarial-challenge). Phase 3 asks questions only; it is not the adversarial-challenge skill.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Craft a single, high-quality GitHub issue from a developer's description of a bug, unexpected behavior, or desired enhancement. Walks through reproduction, codebase exploration, and structured drafting so the issue is actionable on arrival. Use when user wants to file an issue, report a bug, request a feature, or document a problem they've encountered.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Applies depth-driven layered color and shadow principles to elevate average UI into polished, readable interfaces for both light and dark themes. Use when improving or reviewing UI components, setting up a design token system, applying consistent depth and shadow to an interface, or making a flat or inconsistent UI feel more refined without a full redesign.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Autonomous build-verify-fix loop that runs until an explicit Definition of Done passes. Use when named (mini-loop) or when the user says exactly "run a loop".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run a 3-leg evaluation against a newly released LLM. Leg 1 is trap questions with deterministic answers, leg 2 is an agentic orchestration task with a planted failure, leg 3 is a brownfield feature build in a real repo. Use when the user wants to vibe-check, test, evaluate, or compare a new frontier model, or mentions model-bench, model vibe check, or launch-day protocol.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Choose OpenRouter models and routers, query live catalog data, use structured outputs and batch inference, and debug routing with metadata. Use when working with OpenRouter APIs, openrouter/auto, openrouter/free, model discovery, pricing, providers, batch jobs, or structured JSON responses.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
TypeScript and Prisma ORM best practices for schema design, type-safe queries, migrations, and error handling. Use when writing Prisma schemas, building database access layers, or debugging query performance in TypeScript projects.
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Stress-tests ideas by surfacing assumptions, counterarguments, and confidence gaps. Use when evaluating claims, proposals, plans, or decisions that need rigorous intellectual scrutiny.
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Cuts fluff and leads with what matters. Applies Parkinson's Law, Pareto, and Goodhart's Law so every word earns its place. Use when the user wants terse output, names this skill, or signals that responses are too padded.
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Generates as many digits of pi as possible and writes them into files inside a tokenMaxxing/ folder. Use when the user asks to token-maxx, fill a file with pi digits, test agent output throughput, or generate N pi files sequentially or in parallel.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Runs a comprehensive 20-point code quality audit on a "vibe-coded" codebase that was shipped fast and now needs hardening. Use this skill whenever the user mentions vibe coding, vibe audit, code audit, code review, code cleanup, hardening a prototype, productionizing a codebase, technical debt cleanup, or asks Claude to "audit my code", "review my codebase", "clean up my project", or check a freshly-shipped project for common quality issues. Also use when a user shares a repo and asks what's wrong with it or how to make it production-ready.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.