551건 · 관련도순
Diagnose when intuitive judgment, agent confidence, or expert routing can be trusted by classifying environment validity, feedback quality, and task-boundary fit. Use for confidence calibration, agent routing, expertise audits, and escalation design. NOT for deterministic implementation tasks, pure syntax debugging, or domains with explicit verifiable answers.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design low-friction UX, interaction patterns, and comeback loops for AI coding assistant apps, agent consoles, background coding agents, and Port Daddy swarm/operator surfaces. Use when creating flows like prompt-to-diff, context attach, plan/apply/review, checkpoint rollback, background-agent dashboards, visual proof, or multi-agent invocation. NOT for generic landing pages, static dashboards, or implementation-only changes without product flow.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Apply cognitive task analysis to expert work that depends on perceptual cues, branching judgment, and recurring monitoring loops. Use when decomposing expert capability into agent structure, simulation design, or validation interviews. NOT for ordinary step-by-step SOP capture or simple pipelines with no tacit cue layer.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design RL simulation sandboxes, trajectory datasets, QLoRA/LoRA adaptation plans, eval harnesses, and rollback unhooks for agents learning specific coding behaviors beyond the base model. Use when building or reviewing tool-use training loops, offline trajectories, reward functions, self-improvement harnesses, or Port Daddy agent behavior curricula. NOT for generic ML tutorials, full model training operations, or production deployment without eval gates and safety unhooks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Apply AlphaGo-style patterns: learned priors plus search, mixed evaluators, self-play, and asynchronous fast/slow loops. Use for intractable search and compute allocation. NOT for basic supervised learning, tractable optimization, or domains without search bottlenecks.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Redux Toolkit selector rules against re-renders, recalculation warnings, and render loops. Use when writing useSelector/useAppSelector or createSelector, deriving state in a connected component, or seeing 'Selector returned a different result when called with the same parameters'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
自律型Claude Codeループのパターンとアーキテクチャ — シンプルなシーケンシャルパイプラインからRFC駆動のマルチエージェントDAGシステムまで
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Hypothesis-Test Loops via REPL for Exploratory Abductive Inference with Gay.jl colors
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert 3D modeling specialist with deep knowledge of topology, UV mapping, game-ready and film-ready pipelines, DCC tool workflows (Blender, Maya, ZBrush, 3ds Max, Houdini), retopology, LOD systems, and export pipelines. This skill represents years of production experience distilled into actionable guidance. Use when "3d model, 3d modeling, mesh topology, uv unwrap, uv mapping, retopology, retopo, low poly, high poly, subdivision, subdiv, edge flow, edge loops, polygon modeling, box modeling, hard surface, organic modeling, sculpting, zbrush, blender modeling, maya modeling, 3ds max, LOD, level of detail, game ready mesh, film ready, baking normals, high to low, fbx export, gltf export, texel density, 3d, modeling, topology, uv, game-dev, vfx, blender, maya, zbrush, retopology, lod, hard-surface, organic, sculpting" mentioned.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Patterns for continuous autonomous agent loops with quality gates, evals, and recovery controls.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Security review and threat work — threat modeling, vulnerability assessment, penetration test, incident response, OWASP Top 10, LLM Top 10, API Top 10, CVE triage, STRIDE, NIST CSF, SBOM. Auto-loops on any task touching PII, auth, payments or regulated data.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Apply a named behavioral science framework to any task — persuasion, nudge design, habit formation, conversion, influence, negotiation, cognitive bias, choice architecture, decision framing. The framework backbone every other Maxim skill loops into for psychological validation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run a bounded, governed iteration — "loop", "iterate until", "keep going until", "sweep", "ratchet", "until it passes", "coverage to 100". Turns an open-ended autonomous run into a finite loop with checkpoints and explicit stopping conditions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert skill for building web-based game engines and games using HTML5, Canvas, WebGL, and JavaScript. Use when asked to create games, build game engines, implement game physics, handle collision detection, set up game loops, manage sprites, add game controls, or work with 2D/3D rendering. Covers techniques for platformers, breakout-style games, maze games, tilemaps, audio, multiplayer via WebRTC, and publishing games.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Configures AI agents (GitHub Copilot, Claude Code, Cursor, Codex) to understand a codebase and self-improve as the project evolves. Use when setting up a new project for AI-assisted development, onboarding AI agents to an existing repo, creating AGENTS.md, configuring MCP servers for code navigation, packaging project workflows as agent skills, or establishing self-improvement feedback loops. Covers AGENTS.md authoring, skill packaging, MCP configuration, context management, and living-documentation strategies.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Master modern JavaScript with ES6+, async patterns, and Node.js APIs. Handles promises, event loops, and browser/Node compatibility. Use PROACTIVELY for JavaScript optimization, async debugging, or complex JS patterns.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when a Claude Code session loops, drifts from scope, claims a fix that CI rejects, hits context, PATH, or permission walls, or fails in a way another retry will not solve and a root cause diagnosis is needed instead.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Microsoft Entra ID (Azure AD) authentication for React SPAs with MSAL.js and Cloudflare Workers JWT validation using jose library. Full-stack pattern with Authorization Code Flow + PKCE. Prevents 8 documented errors. Use when: implementing Microsoft SSO, troubleshooting AADSTS50058 loops, AADSTS700084 refresh token errors, React Router redirects, setActiveAccount re-render issues, or validating Entra ID tokens in Workers.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Make your AI agent learn and improve automatically. Reviews sessions, extracts learnings, updates memory files, and compounds knowledge over time. Set up nightly review loops that make your agent smarter every day.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Complete community building, engagement, and monetization system. From zero to thriving community — launch strategy, member engagement loops, content programming, moderation frameworks, growth tactics, monetization models, and health metrics. Works for Discord, Slack, Telegram, Circle, forums, or any platform.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.