「can」の検索結果

Runs GitHub Actions workflows on your own machine in Docker containers with act, so CI can be tested without pushing. Use when a user asks to test GitHub Actions workflows locally, debug a failing CI pipeline, pass secrets or inputs to a local run, or run workflows offline.

日本語の概要は準備中です。原文の説明を表示しています。

Analyze indexed codebases via graph database (neug) and vector index (zvec). Covers call graphs, dependencies, dead code, hotspots, module coupling, architecture reports, semantic search, impact analysis, bug root cause from GitHub issues, class diagrams (UML), and PR review (risk scoring, conflict detection, auto-merge candidates, labeling). Also covers creating, inspecting, and repairing a CodeScope index. Use for: code structure, who calls what, why something changed, similar functions, module boundaries, bug tracing, class relationships, PR risk/conflicts, or any question benefiting from a code knowledge graph. Applies when a `.codegraph` index exists in the workspace, or when the user wants to create one.

日本語の概要は準備中です。原文の説明を表示しています。

当用户需要把内容（文章、笔记、截图、数据、产品说明）做成中文图文卡片组图时使用——小红书 / Rednote 3:4 竖图、公众号封面、社交卡。提供三套独家视觉语言（静纸 Still Paper本手记 / Signal Proof 证据层 / Bridge Canvas 跨平台桥），由 Claude 读懂内容、自己撰写 brief.json，交给确定性引擎渲染出第一眼惊艳、一眼可辨、国内开箱即用的图文组图。

日本語の概要は準備中です。原文の説明を表示しています。

Expert in creating rich backstories, fictional universes, and ARGs (Alternate Reality Games). Covers world-building, mystery construction, community-driven storytelling, and transmedia narratives. Knows how to create depth that rewards exploration without overwhelming. Use when "lore, world building, backstory, ARG, mythology, fictional universe, hidden story, deep canon, " mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

I am a veteran print production specialist with 15+ years in tabletop game manufacturing. I've shepherded hundreds of games from digital files to retail-ready products, working with manufacturers from The Game Crafter to Panda GM to Cartamundi. My expertise spans the entire production pipeline: color management, dieline creation, paper selection, finishing techniques, component nesting, insert design, and the critical art of the unboxing experience. I've learned the hard way about RGB-to-CMYK disasters, registration drift, humidity warp, and minimum font sizes that become illegible smudges. I know the difference between 280gsm blue-core and 320gsm black-core card stock by feel. I can tell you why your rich black needs to be C60-M40-Y40-K100, not just K100. I understand why your box needs 15mm clearance on each dimension, and why that gorgeous neon green in your design will become a muddy olive in print. Use when "print my game, packaging design, prepare files for print, dieline, print specifications, board game manufacturing, card game printing, box design, bleed and safe area, CMYK conversion, paper stock, card finish, foil stamping, embossing, unboxing experience, thermoform insert, punchboard design, component manufacturing, Panda GM, Game Crafter, Cartamundi, print-production, packaging, manufacturing, board-games, card-games, cmyk, dieline, die-cutting, offset-printing, tabletop" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Go is the language of infrastructure. From Docker to Kubernetes to the entire cloud-native ecosystem, Go powers the systems that run the internet. It's not about what you can build - it's about what you won't break at 3 AM. This skill covers idiomatic Go patterns, error handling, concurrency with goroutines and channels, HTTP servers, microservice architecture, and the standard library that makes Go so powerful. Key insight: Go's simplicity is a feature. Fight the urge to abstract. Embrace boring, readable code. 2025 lesson: The teams succeeding with Go are the ones who resist overengineering. A main.go with 500 lines beats a "clean architecture" with 50 packages. Use when "golang, go service, go microservice, goroutine, channels, go http, go api, go backend, gin, fiber, chi router, go concurrency, go, golang, microservices, backend, concurrency, goroutines, channels, http, api" mentioned.

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Expert in live learning experiences - cohort-based courses, workshops, webinars, coaching sessions, and real-time facilitation. Covers designing for synchronous learning, building peer accountability, and creating transformative live experiences that self-paced courses can't match. Use when "cohort course, live course, workshop, webinar, group coaching, live session, cohort-based, " mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Master the AI tools that transform hiring and HR operations. From sourcing candidates to onboarding, find and retain great talent faster. Use when "hiring, recruiting, HR, talent, performance management, hr, recruiting, hiring, talent, people" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

GraphQL gives clients exactly the data they need - no more, no less. One endpoint, typed schema, introspection. But the flexibility that makes it powerful also makes it dangerous. Without proper controls, clients can craft queries that bring down your server. This skill covers schema design, resolvers, DataLoader for N+1 prevention, federation for microservices, and client integration with Apollo/urql. Key insight: GraphQL is a contract. The schema is the API documentation. Design it carefully. 2025 lesson: GraphQL isn't always the answer. For simple CRUD, REST is simpler. For high-performance public APIs, REST with caching wins. Use GraphQL when you have complex data relationships and diverse client needs. Use when "graphql, graphql schema, graphql resolver, apollo server, apollo client, graphql federation, dataloader, graphql codegen, graphql query, graphql mutation, graphql, api, apollo, schema, resolvers, dataloader, federation, typescript" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Git is deceptively simple to learn and incredibly hard to master. The difference between a team that ships and a team that fights merge conflicts all day comes down to workflow discipline. Your git history is documentation - make it tell a story future you can understand. This skill covers branching strategies (trunk-based, gitflow, GitHub flow), commit hygiene, merge vs rebase, conflict resolution, and the commands you actually need. Key insight: most git disasters come from not understanding what you're about to do. 2025 lesson: Trunk-based development with short-lived branches has won. Long-lived feature branches are a code smell. If a branch lives more than a few days, something is wrong with your architecture or process. Use when "git workflow, branching strategy, git merge, git rebase, merge conflict, git commit, trunk-based, gitflow, git history, git revert, git reset, git, version-control, workflow, branching, commits, merge, rebase, collaboration" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Raising money is a means to an end, not the end itself. Great companies can be built with or without venture capital. But if you're raising, you need to understand the game: when to raise, how much, from whom, and at what terms. This skill covers fundraising timing, process, pitch construction, term sheet negotiation, and investor relationship management. It's not about raising as much as possible - it's about raising strategically. Use when "fundraising, raising money, pitch deck, investors, term sheet, valuation, dilution, series A, seed round, pre-seed, runway, cap table, VC, venture capital, fundraising, investors, venture-capital, pitch-deck, term-sheet, valuation, dilution, seed, series-a, cap-table" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Docker makes "works on my machine" a deployment strategy. Package your app with its dependencies, run it anywhere. But Docker's simplicity hides real complexity. A naive Dockerfile can be 10x larger and slower than it needs to be. This skill covers Dockerfile optimization, multi-stage builds, Docker Compose for development, security hardening, and production patterns. Key insight: your Dockerfile is code. Review it, optimize it, version it. 2025 lesson: Containers aren't VMs. The patterns that work for VMs (install everything, big base images) are anti-patterns for containers. Think small, think immutable, think layers. Use when "docker, dockerfile, container, docker compose, docker build, containerize, docker image, multi-stage build, docker network, docker volume, docker, containers, devops, deployment, infrastructure, security, optimization" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Paul Graham's founder mode. When to delegate vs. dive deep. Maintaining velocity as you scale. Avoiding "professional CEO" traps. The operating mode that built Apple, Tesla, and every YC unicorn. Founder mode isn't micromanagement - it's having the conviction and context to make decisive moves that employees can't. It's staying in the arena when conventional wisdom says to step back. Use when "founder mode, should i delegate, staying close to work, micromanagement, when to step back, professional ceo, manager vs founder, skip level, how involved should i be, letting go of control, scaling as founder, founder burnout, founder, leadership, delegation, management, scaling, operational" mentioned.

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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% by step 10. Build for reliability first, autonomy second. 2025 lesson: The winners are constrained, domain-specific agents with clear boundaries, not "autonomous everything." Treat AI outputs as proposals, not truth. Use when "autonomous agent, autogpt, babyagi, self-prompting, goal decomposition, react pattern, agent loop, self-correcting agent, reflection agent, langgraph, agentic ai, agent planning, autonomous, agents, langgraph, react, planning, reflection, guardrails, reliability, checkpointing" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Expert in designing and implementing visceral, satisfying combat systems. Masters hitbox/hurtbox design, frame data, combo systems, enemy archetypes, damage feedback, and the invisible craft that makes players feel powerful. Draws from fighting games, character action games (DMC, Bayonetta), and Souls-like design to create combat that is readable, responsive, and endlessly replayable. Use when "combat system, combat design, hitbox, hurtbox, frame data, hitstop, screen shake, input buffer, coyote time, i-frames, invincibility frames, combo system, attack cancel, recovery frames, punishment window, souls-like combat, action game combat, fighting game, damage feedback, enemy design, boss design, attack telegraph, parry system, stamina system, poise system, weapon feel, game feel combat, melee combat, combat juice, combat, action-game, fighting-game, hitbox, frame-data, game-feel, souls-like, character-action, melee, enemy-design, boss-design, combo, parry, i-frames" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

World-class continuous integration and deployment - GitHub Actions, GitLab CI, deployment strategies, and the battle scars from pipelines that broke productionUse when "ci/cd, cicd, pipeline, github actions, gitlab ci, circleci, jenkins, workflow, deployment, deploy, release, blue green, canary, rollback, build, test automation, continuous integration, continuous deployment, cicd, github-actions, gitlab-ci, deployment, automation, devops, pipelines, continuous-integration, continuous-deployment" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

CI/CD is the backbone of modern software delivery. Continuous Integration catches bugs early. Continuous Deployment gets features to users fast. But poorly designed pipelines can be slow, flaky, and a source of constant frustration. This skill covers GitHub Actions (the most popular), GitLab CI, and general pipeline design principles. The focus is on pipelines that are fast, reliable, and maintainable. 2025 reality: Your pipeline is infrastructure code. It deserves the same care as your application. A flaky test in CI is worse than no test - it teaches developers to ignore failures. Use when "github actions, gitlab ci, ci cd, pipeline, workflow, deploy automation, continuous integration, continuous deployment, build pipeline, yaml workflow, ci-cd, github-actions, gitlab-ci, devops, automation, deployment, pipelines" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Your most loyal users aren't just customers - they're potential advocates, contributors, and community members who can become the engine of your growth. Community-led growth isn't about broadcasting to an audience - it's about creating a space where your users connect with each other, share knowledge, and become invested in your success. This skill covers community strategy, platform selection, engagement tactics, ambassador programs, and the metrics that matter. Whether you're building a Discord for developers or a forum for power users, the goal is the same: creating genuine value that makes members want to stay and contribute. Use when "community, discord, forum, user group, ambassador, champions, developer relations, devrel, community engagement, community growth, power users, superfans, community, discord, engagement, devrel, ambassador, forum, user-community, growth, retention, champions" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

World-class color theory expertise combining the scientific precision of Josef Albers' "Interaction of Color," the systematic thinking of color systems from Pantone and RAL, and the perceptual psychology insights from researchers like Bevil Conway. Color is not just aesthetics - it's communication, emotion, and usability compressed into wavelengths. Great color work is invisible when done right. Users don't notice "nice colors" - they notice when they can't read text, when buttons don't look clickable, when errors don't feel urgent, or when the interface feels "off" without knowing why. Color theory is the science of making the right thing feel obvious. Use when "color theory, color palette, color scheme, color harmony, complementary colors, analogous colors, contrast ratio, dark mode colors, light mode, color tokens, semantic colors, color accessibility, color blindness, color psychology, color system, brand colors, data visualization colors, color, design, accessibility, contrast, dark-mode, theming, tokens, wcag, palette, harmony" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

The new frontier of audio: AI-generated music with Suno and Udio, AI sound effects with ElevenLabs, AI voice cloning, and AI audio enhancement. This skill covers the full spectrum of neural audio synthesis and manipulation. We're in an era where a single person can produce broadcast-quality audio content that would have required studios, musicians, and engineers. AI doesn't replace musical talent—it democratizes production capability. Original compositions in minutes. Custom sound design in seconds. Voice in any language instantly. The practitioners of this skill understand both the creative potential and the ethical considerations. They know when AI audio enhances creativity and when it needs human touch. They're audio directors who orchestrate AI tools like instruments in a symphony. Use when "AI music, generate music, Suno, Udio, AI audio, AI sound, generate soundtrack, background music, sound effects, audio generation, jingle, AI score, stem separation, ai-audio, music, suno, udio, sound-effects, soundtrack, generation, audio-branding, production" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

World-class expertise in measuring, attributing, and optimizing AI-generated content performance. Combining data science rigor with content strategy intelligence to answer the questions traditional content analytics can't: Is AI content performing? Which AI variations convert? What's the true ROI of AI vs traditional content creation? This isn't vanity metrics for robots. This is the discipline of proving AI content drives business outcomes - and using that data to make AI content systems better, faster, and more profitable. Built on the principles of companies like Jasper, Copy.ai, and Notion who've scaled AI content operations with measurement as the foundation. Use when "ai content performance, ai content analytics, measure ai content, ai content roi, ai vs human content, ai content attribution, ai content testing, ai variation testing, ai content dashboard, ai content metrics, prompt performance, ai content conversion, ai content quality score, content velocity, ai content efficiency, ai-content, analytics, measurement, attribution, roi, ab-testing, performance, optimization, data-driven, content-analytics" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

The orchestration layer for AI-native creative production. This skill coordinates multiple AI tools—video, image, audio, digital humans, effects—into cohesive campaigns, productions, and creative systems. As AI tools proliferate, the challenge shifts from "can we create this?" to "how do we orchestrate these capabilities into something coherent?" The AI Creative Director thinks in systems, not tools. In pipelines, not one-offs. In brand consistency across AI-generated assets. This is where creative vision meets technical orchestration. The AI Creative Director doesn't just use AI tools—they compose them into creative instruments that produce at scales and speeds previously impossible. Use when "AI creative director, orchestrate AI, AI campaign, multi-tool, AI workflow, AI pipeline, coordinate AI, AI production, AI creative system, full AI production, AI at scale, orchestration, creative-direction, ai-production, workflow, pipeline, multi-tool, scale, quality-control" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragmented with inconsistent terminology. We use the CoALA cognitive architecture framework: semantic memory (facts), episodic memory (experiences), and procedural memory (how-to knowledge). Use when "agent memory, long-term memory, memory systems, remember across sessions, memory retrieval, episodic memory, semantic memory, vector store, rag, langmem, memgpt, conversation history, memory, vector-store, rag, retrieval, embedding, episodic, semantic, procedural, langmem, memgpt, pinecone, qdrant, chromadb" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

Mastery of AI image generation across the full spectrum: Midjourney for aesthetic perfection, Flux for prompt adherence, DALL-E 3 for concept clarity, Stable Diffusion for control, and Imagen 3 for photorealism. This skill transforms text into visual reality at the speed of thought. We've moved beyond "AI can make pictures" to "AI is the fastest concept artist, product photographer, and visual designer ever created." The skill isn't just prompting—it's understanding how each model thinks, what makes images work, and how to systematically produce exactly what you envision. The best AI image generators have internalized composition, lighting, color theory, and style—not by studying art, but by generating thousands of images and learning what works. They're visual directors who happen to work in text. Use when "AI image, generate image, Midjourney, DALL-E, Flux, Stable Diffusion, Imagen, text to image, AI art, AI photo, AI illustration, AI visual, AI graphics, generate picture, ai-image, midjourney, dall-e, flux, stable-diffusion, imagen, generation, text-to-image, visual, art" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。