Claude Code 플러그인
공개 Claude Code 마켓플레이스의 플러그인 8개입니다. 각 플러그인은 함께 설치되는 스킬, 슬래시 명령, 에이전트, 훅 또는 MCP 서버를 묶습니다.
필터와 일치하는 8개의 플러그인을 표시합니다. 필터 초기화
Enterprise / cross-functional Research Operations domain — the managed counterpart to the academic research/ domain. v2.9.0 ships 5 skills: orchestrator (context: fork), clinical-research (protocol synopsis, endpoint selection, sample-size/power for means/proportions/survival, phase-gate feasibility), research-finance (R&D budgeting with F&A split, burn/runway, capitalize-vs-expense routing, portfolio ROI), market-research (TAM/SAM/SOM top-down and bottoms-up, survey sampling with FPC, Kotler segmentation), and product-research (goal-matched study design, method-based saturation, insight synthesis flagging single-source anecdotes). Hard rules: outputs are estimates routed to a named clinical or finance owner, market sizes show method + assumptions, product insights require recurrence across independent participants. 24 stdlib Python tools, 12 reference docs. Distinct from ra-qm-team, finance, research/grants, product-team, and marketing-skill.
NIH grant-funding intelligence skill. RePORTER/NOSI/study-section navigation, R01/R21/K-award strategy. Research-pack convention. Path-B from megaprompt 11.
Research orchestrator (hybrid router + fallback). Deterministic SIGNALS classification routes to 6 specialists (pulse/litreview/grants/dossier/patent/syllabus) at >=2 signals, else runs own 8-step plan-decompose-search-synthesize-cite fallback. Routing transparency mandatory. Path-B from megaprompt 13.
Scientific and research paper writing, grants, peer review, critical appraisal.
research
Scientific writing, citations, grants, posters, and academic career (14 skills)
Six skills for scientific writing: edit research prose, structure an IMRaD manuscript, run the writing process, handle peer review and publication ethics, draft grants and letters, and write for general audiences.
writing
Open WebUI operator suite — REST API administration (v0.10.x: user/group lifecycle, model catalog GitOps via models/sync, config-as-code, SCIM, event webhooks, the 0.10.0 access_control→access_grants break, auth traps), RAG pipeline wiring (HuggingFace embedding + reranker via LiteLLM in front of HuggingFace Text Embeddings Inference; exact wire shapes, LiteLLM ↔ TEI gotchas, TEI configuration cliffs, end-to-end production config; BGE-M3 + BGE-Reranker-v2-m3 worked examples) and multi-pod deployment with WebSockets + Valkey Sentinel at 1000+ user scale (the structural Socket.IO + Redis frame-amplification bug #23733 and the CHAT_RESPONSE_STREAM_DELTA_CHUNK_SIZE mitigation, all multi-pod env vars, custom-model-icon perf history, helm chart gaps, full known-issues catalog with fix status).
ai-workflow
Implement and deliver an authorized change end to end — verify, open the PR, merge, and confirm post-merge state — using live-state gates, durable interruption handoffs, and live-state-first resumption. Use when a user grants end-to-end delivery authority for a specific change and the work may cross tool-call limits, context exhaustion, worker loss, or session interruptions before the delivery boundary is reached. Do not use for plain fixes with no delivery directive, for granting merge or post-merge authority the user did not grant, or for designing release pipelines (use release-engineering for that).
