2.6천건 · 관련도순
Use for Nauthilus native Go plugin API design or implementation, `pluginapi/v1`, plugin loader, plugin registry, plugin runtime, reload integration, plugin config, extension-point parity with Lua, capability-based host services, lifecycle semantics, and the working draft under `server/docs/go_plugin_api_working_draft.md`.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Plan FriendlyBet ethical growth, SEO, README positioning, open-source contribution paths, self-hosting story, public trust, and discovery without ads, trackers, spam, or dark patterns. Use for repo-facing docs, growth strategy, launch positioning, SEO pages, contributor onboarding, or public messaging.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Control FriendlyBet operating cost, free-tier viability, provider/API cost, GitHub Actions/Supabase/Vercel usage, documentation hygiene, company memory updates, playbook maintenance, and skill validation. Use when evaluating cost, operational burden, tooling, internal docs, company memory, or whether agent profiles should become full skills.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate or refresh docs/ARCHITECTURE.md from current codebase state with evidence-backed component and data-flow mapping
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Document templates for all pipeline output documents — specs, indexes, reports, and strategy docs. Use when any workflow needs to produce a structured document.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
How to run and test the docs/index.html AGSL shader web gallery locally (static server, WebGL2-capable Chrome flags, CDP verification hooks).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Coda — coda document management covering docs, pages, tables, formulas, and workspace analytics. Use when auditing Coda workspace usage, managing documents and tables, querying structured data, or analyzing collaboration patterns across a Coda organization.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when working with Great Expectations — great Expectations data quality framework analysis. Covers expectation suite management, validation result review, data docs generation, checkpoint execution, datasource configuration, and batch analysis. Use when reviewing data quality results, managing expectation suites, investigating validation failures, or auditing data quality configurations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Eliminates AI-generated writing patterns that erode reader trust. Use when writing or editing articles, docs, or press releases.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use for Vercel cost and performance optimization on deployed projects, especially Next.js, SvelteKit, Nuxt, and limited Astro apps. Collect Vercel metrics, usage, project config, and code scan results first; investigate only metric-backed candidates; produce ranked recommendations grounded in verified files and version-aware Vercel/framework docs. Trigger for Vercel bill reduction, slow or expensive routes, caching opportunities, Function Invocations, Build Minutes, Fast Data Transfer, Core Web Vitals, Bot Management, Fluid compute, or cost breakdown requests.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Word (.docx) manipulation via MCP server. Use for reading, creating, editing, formatting Word documents including tables, footnotes, comments, images, headers, styles, and PDF conversion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Microsoft docs lookup, code samples, and SDK reference for Azure, .NET, Microsoft 365, Windows, and Power Platform via Microsoft Learn MCP. Use for API reference or official MS documentation retrieval.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when tasks involve reading, creating, or reviewing PDF files where rendering and layout matter; prefer visual checks by rendering pages (Poppler) and use Python tools such as `reportlab`, `pdfplumber`, and `pypdf` for generation and extraction.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
PowerPoint (.pptx) manipulation via MCP server. Use for creating slides, formatting presentations, managing placeholders, adding images, applying templates, or extracting text from .pptx files.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Audit and rewrite content to remove AI writing patterns ("AI-isms"). Supports detect-only audits, edit-in-place file cleanup, voice and context profiles, and an iterate-to-convergence pass.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Map tasks to specialist agents. Use when choosing which agent for a job, comparing agent capabilities, or routing to React/Next.js/Playwright/docs/code-quality experts. Keywords: which agent, best agent for this, delegate to expert, agent capability mapping.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Automate doc generation with JSDoc/TSDoc, linters, and pre-commit hooks. Use when setting up markdownlint, configuring doc linting pipelines, integrating JSDoc/TSDoc, or building automated documentation workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Evaluate and improve AI-generated output with explicit rubrics, reflection loops, and stop conditions. Use when building self-critique workflows, evaluator-optimizer pipelines, or acceptance gates for code, docs, analysis, or plans.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Design philosophy docs and canvas-based visual creation. Use when articulating design principles, crafting multi-page design documents, or exploring aesthetic philosophy with intentional design thinking.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Documentation quality standards and writing principles. Use when establishing formatting rules, reviewing doc quality metrics, creating writing guidelines, or enforcing consistent documentation style across a project.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Python research assistant with Context7 MCP. Use for Python library research, evaluating packages, enforcing strict Python coding standards, or fetching up-to-date library docs via Context7.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Turn any codebase into a beautiful, interactive single-page HTML course that teaches how the code works to non-technical people. Use this skill whenever someone wants to create an interactive course, tutorial, or educational walkthrough from a codebase or project. Also trigger when users mention 'turn this into a course,' 'explain this codebase interactively,' 'teach this code,' 'interactive tutorial from code,' 'codebase walkthrough,' 'learn from this codebase,' or 'make a course from this project.' This skill produces a stunning, self-contained HTML file with scroll-based navigation, animated visualizations, embedded quizzes, and code-with-plain-English side-by-side translations.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.