공개 Claude Code 마켓플레이스의 플러그인 17개입니다. 각 플러그인은 함께 설치되는 스킬, 슬래시 명령, 에이전트, 훅 또는 MCP 서버를 묶습니다.
필터와 일치하는 17개의 플러그인을 표시합니다.
magnus-agent-skillsmagnus919/agent-skills2
claude-code-skillsalirezarezvani/claude-skills1
pm-claude-skillsmohitagw15856/pm-claude-skills1
ultralyticsultralytics/skills1.claude-plugin/marketplace.json이 포함된 repo를 제출하면 모든 plugin을 목록에 추가합니다.
marketplace 제출Convert long markdown files into world-class single-file interactive HTML — DOMAIN COMPLETE at v2.10.3 (5 skills). v2.10.3 adds md-slides, the slide-deck converter (arrow/Space/PgDn/Home/End/P navigation, presenter mode with clock + speaker notes + next-slide preview, URL-hash deep linking, @media print page-per-slide for browser-native PDF export; vanilla JS only; Prism.js opt-in via --syntax). Joins md-review (v2.10.2 code-review converter: 2-col diff, severity-tagged margin annotations, WCAG-1.4.1 badges, named reviewer footer), md-document (v2.10.1 long-form: sticky TOC, scrollspy, search, code-copy, Prism autoloader), markdown-html-orchestrator (v2.10.0 context: fork; deterministic doc-type classifier), and design-system (v2.10.0 onboarding wizard; WCAG-AA 12-token palette). 15 stdlib-only Python tools, 15 references, 4 template assets. Inspired by Thariq Shihipar's Claude Code HTML output essay.
Figma skills for PMs and designers: Component Audit, Design Brief, Annotation Guide, Design Review, User Flow Planner, Variant Matrix, Spacing System, Prototype Plan, Design QA, PM Design Critique. Work smarter across the full Figma design lifecycle.
Agent skills for Ultralytics YOLO and Platform: model selection, dataset annotation, training, tuning, inference, export, and deployment through the Platform web UI, the Python package, and the yolo and ul CLIs.
developmentArize AX platform skills for LLM observability, evaluation, and optimization. Includes trace export, instrumentation, datasets, experiments, evaluators, AI provider integrations, annotations, prompt optimization, and deep linking to the Arize UI.
12 working methods for realtime collaboration: collaborative-editing-models, comments-and-annotations, conflict-resolution-ux, live-cursors-and-selection, and more
Official Koin skills: set up Koin, write Koin code, migrate from Hilt, Dagger, Toothpick, Kodein or older Koin, and diagnose Koin apps with Kotzilla. Koin 4.x with the Koin Compiler Plugin — Annotations (JSR-330 compatible) or DSL, compile safe in both, Kotlin Multiplatform.
Capture, annotate, and embed screenshots and animated GIF demos in pull request descriptions. Includes Playwright-based UI capture, PIL image annotations, PR embedding workflows for GitHub and Azure DevOps, and screen recording with variable timing.
Operate, configure, provision, secure, and troubleshoot Grafana OSS, Enterprise, and Cloud, including dashboards, folders, data sources, annotations, alert rules, contact points, notification policies, silences, mute timings, service accounts, RBAC, plugins, APIs, and as-code workflows. Use for Grafana product work and Grafana-side integrations. Do not use for defining SLOs or paging policy, operating Prometheus/Loki/Tempo/InfluxDB backends, generic Docker/Kubernetes/Terraform/reverse-proxy work, plugin development, or authorized security assessments; use the corresponding specialist skill.
Design and improve human annotation programs for machine-learning training, validation, and evaluation data, including task and label schemas, active acquisition, annotator guidance, calibration, disagreement, adjudication, provenance, and cost-quality stopping. Do not use for general statistical inference, data storage pipelines, model training, or annotation-interface implementation; route those concerns to data-scientist, data-engineering, ml-engineering, or product-design-and-ux.
Annotate and review real HTML DOM, export AI-ready feedback context, inspect elements, and capture reproducible prototype states.
File images and other assets into Eagle (eagle.cool) libraries through the local API with consistent folders, names, tags and annotations; move items between libraries without breaking the Obsidian notes that link to them; check and repair those links; export Eagle folders into projects; and keep one Obsidian note per asset for a Bases image gallery.
Use when you need to add or evaluate Maven dependencies that improve code quality — including nullness annotations (JSpecify), static analysis (Error Prone + NullAway), functional programming (VAVR), or architecture testing (ArchUnit) — and want a consultative, question-driven approach that adds only what you actually need.
Use when you need to review, improve, or write Java unit tests — including migrating from JUnit 4 to JUnit 5, adopting AssertJ for fluent assertions, structuring tests with Given-When-Then, ensuring test independence, applying parameterized tests, mocking dependencies with Mockito, verifying boundary conditions (RIGHT-BICEP, CORRECT, A-TRIP), leveraging JSpecify null-safety annotations, or eliminating testing anti-patterns such as reflection-based tests or shared mutable state.
Use when you need to review, improve, or build Spring Boot 4.0.x applications — including proper usage of @SpringBootApplication, component annotations (@Controller, @Service, @Repository), bean definition and scoping, configuration classes and @ConfigurationProperties (with @Validated), component scanning, conditional configuration and profiles, constructor injection, @Primary and @Qualifier for multiple beans of the same type, bean minimization, graceful shutdown, virtual threads, Jakarta EE namespace consistency, and scheduled tasks.
Use when you need to design, review, or improve REST APIs with Micronaut — including @Controller routes, HTTP status codes, DTOs, Bean Validation, exception handlers, pagination, idempotency, ETag/If-Match, caching headers, versioning, contract-first OpenAPI (OpenAPI Generator), optional runtime OpenAPI via micronaut-openapi, and security annotations.
Use when you need programmatic JDBC in Micronaut — pooled DataSource, parameterized SQL, io.micronaut.transaction.annotation.Transactional, batching, and domain exception translation.
ASB Metabolomics. Computational metabolomics (predominantly LC-MS/MS; also LC-MS, GC-MS, NMR, mass-spectrometry imaging, ion mobility, lipidomics, multi-omics): spectral library matching, molecular networking, formula/structure annotation (SIRIUS), preprocessing, normalization, and statistics: 11,830 evidence-grounded skills over 1,989 tools, each derived from a method paper (journal article or preprint) and its code. Router-shaped: one skill is advertised (the router); the corpus ships as data and is retrieved on demand, so installing costs negligible context. It carries the grounding map `kb_bundle.json`, but not the Perspicacité grounding binder.
