'paper' 검색 결과

Knowledge pack from 'Towards Digital Engineering: The Advent of Digital Systems Engineering' (Huang et al., Old Dominion University, arXiv:2002.11672, 2020). Use when reasoning about digital engineering, the DoD Digital Engineering Strategy and its five goals, the Authoritative Source of Truth, digitalization vs. digitization, digital augmentation, digitalized models, provenance, unique identification, and the four-level (vision/strategy/action/foundation) DSE research framework. Covers the conceptual/vision layer of the field. SCOPE LIMITS: this is a single ~28-page vision paper, not a methods handbook — it is thin on step-by-step procedures, tooling, case studies, and quantitative evaluation, and it predates 2020 so it does not cover later digital-engineering standards or recent AI/LLM advances. Use the sebok pack for established SE canon and MBSE depth.

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A relentless interview to sharpen a plan or design. Use when the user says "grill me", "grill mich", "grill mich zu diesem Plan", or explicitly invokes /grill-me. Does NOT fire on generic "review this", "poke holes", "stress-test", "devil's advocate" or "critique" phrasing -- for reviewing an already-written artifact (code, PR, paper) use code-review, 3agenten-review, 7phasen-review or caveman-review instead; grill-me interrogates a still-open plan or idea before it is built.

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Structured 6-step procedure for improving, renovating, or rebuilding existing pipelines, individual project folders, documentation structures, or software stacks. Addressable as "pipeline optimizer" (for whole topic pipelines, e.g. a software, research, or game-dev pipeline) or "project-folder optimizer" (for individual project folders within a pipeline, e.g. a single software tool or paper project). Triggers on tasks like "improve pipeline X", "optimize the stack", "rebuild Y", "renovation", "pipeline refactoring", "clean up project folder", "improve folder structure", "unify conventions", "documentation consolidation", "integrate into existing system", or any substantial intervention in established structures. Delivers building-stock analysis, purpose clarification, ideal sketch, gap plan, empirical pain-point identification, and retests with fresh subagents. Prevents parallel standards, duplication, and pipeline breaks.

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Transform a supplied photo into an editorial collage where a realistic foreground gradually continues as fine drawing and light pigment on paper. Use for 实景渐绘拼贴、摄影与建筑线描融合、photo-to-sketch travel posters. Keeps a photographic anchor rather than converting the whole image into an illustration.

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Turn supplied photos into a refined open photo-book spread image with source-aware crops, restrained typography and tactile paper. Use for 照片记忆册、照片书册效果、editorial memory album images or an open photo-book mockup, not an interactive flipbook application.

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Pair a source-faithful photographic upper panel with a small source-derived dry-brush illustration surrounded by generous paper whitespace below. Use for 摄影加极简手绘、上下双联艺术海报、photo and miniature illustration diptychs or quiet photo-poetry prints.

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Operating NV oOS WordPress sites through scoped MCP operator credentials — tool groups, task recipes, and site disambiguation. Use when working with NV oOS tools (create_post, woo_products, toolkit_cpt, paper_store, jetengine) on any managed site.

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Research products via AI tools, cross-reference live stock, generate WooCommerce-ready copy, and extract marketing angles. Covers the full research-to-copy pipeline with remote_wp_connection stock checks and paper_store persistence. Use when researching products by SKU/name/category, generating WooCommerce descriptions, preparing product data for campaigns, or cross-referencing catalog files against live inventory.

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Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review, devil's advocate challenges, ethics review, and post-research literature monitoring. Triggers on: research, deep research, literature review, systematic review, meta-analysis, PRISMA, evidence synthesis, fact-check, guide my research, help me think through, 研究, 深度研究, 文獻回顧, 文獻探討, 系統性回顧, 後設分析, 事實查核, 引導我的研究, 幫我釐清, 幫我想想, 我不確定要研究什麼, 研究方向, 研究主題.

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Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

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Search and retrieve preprints from arXiv via the Atom API. Use this skill when searching for papers in physics, mathematics, computer science, quantitative biology, quantitative finance, statistics, electrical engineering, or economics by keywords, authors, arXiv IDs, date ranges, or categories.

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Improve the clarity and voice of AI-assisted academic writing (papers, theses, rebuttals) and

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Use Hugging Face Hub via MCP server tools. Search models, datasets, Spaces, papers. Get repo details, fetch documentation, run compute jobs, and use Gradio Spaces as AI tools. Available when connected to the HF MCP server.

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Review a change, module, or surface for exploitable defects — trust boundaries, authn/authz, injection, secret exposure, filesystem and network reach, dependency risk. Use when the user asks for a security review, audit, or vulnerability check of concrete code. Not for general code review, lint, or compliance paperwork.

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Use when acting as the orchestrator agent that drives Syntropic137 - running the dogfood loop, deciding what to dispatch next, landing agent PRs, deploying a beta, triaging failed executions, or keeping the scratchpad, paper cuts and retrospectives current. Trigger phrases include "orchestrator tick", "keep the loop running", "what should we dispatch next", "land these PRs", "why are PRs stacking up", "deploy the next beta", "pit stop", "the run failed, what now", "write the retro", "is the system helping", "scale quality", "learning loop for the orchestrator". Do NOT use for deciding whether one task belongs in a workspace or locally (see `dogfooding`), for turning one incident into an eval case (see `learning-loop`), for designing a workflow A/B experiment (see `workflow-experimentation`), or for release-branch and version-bump mechanics (see `devops`).

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Use when turning something that happened into something that makes the next run better - "write a retro", "record this paper cut", "this bug escaped verification", "make this an eval", "why do we keep hitting this", "did that change actually help", "scorecard", "what did we learn from that run", "lessons keep getting re-learned". Covers the six-step loop (capture, classify, convert, change, measure, retro), the repo artifact each step produces, and how escaped bugs become eval cases. Do NOT use to design or judge a single workflow experiment (see `workflow-experimentation`, which this loop feeds), to decide where to run work (see `dogfooding`), or to debug one failed execution in the moment.

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Search arXiv papers by keyword, author, category, or ID.

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Add a new journal to the MedSci Skills profile database. Extracts metadata from author guidelines, generates write-paper (detailed) and find-journal (compact) profiles in canonical format with quality gates.

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変更内容を確認し、論理的な単位で複数のコミットに分けて実行します

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当使用者说“这篇建模论文还能怎么提升”“按评分表排修改优先级”“时间不够先改什么”“给我一个论文改进清单”“要不要再加一个高级模型”时使用。基于现有草稿、模型工作包、批判 findings、评分规则和真实剩余资源建立可定位的 gap register，再按结论影响、评分关联、工作量、依赖与失败风险排序；每项写所需数据/代码/作者决定、验证与验收条件，先给一个最小可行修订，不用装饰复杂度替代证据，不编创新、实验或评委偏好。

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当使用者说“整理建模论文 LaTeX”“修编译错误和引用”“统一公式、表格和图注”“按比赛模板排版”“检查交叉引用与缺图”时使用。先冻结内容并做基线编译，再在不改变数学含义、数字、引用或作者措辞的前提下修结构、符号格式、标签、表图、文献与版面；运行静态检查和实际编译，记录引擎、命令、警告与输出。只格式化和诊断，不补造公式、结果、来源或论文内容。

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当使用者说“帮我整理建模论文结构”“这一段该放哪”“论文逻辑很乱”“怎么从模型讲到结论”“摘要和正文对不上”时使用。基于学生已有题面、模型、运行、图表和草稿建立主张—证据图，再给按问题驱动的章节蓝图、段落职责、图表计划与页数预算；保证摘要数字可追溯、结果与验证分开、结论强度不越过证据，不代写整篇竞赛论文，不用流畅叙事掩盖缺失分析。

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Ask a few focused questions to define a goal, checkable finish conditions, evidence of completion, and constraints. Use when the user wants help clarifying what success means before doing the work.

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Structure any communication artifact — documents, reports, plans, issue comments, PR descriptions, emails, presentations, slides, charts, and dashboards — using Jean-luc Doumont's "Trees, Maps, and Theorems" method. Use whenever the goal is to get a message across to a busy audience, when asked to improve clarity or structure of writing or slides, or when a deliverable will be judged by whether readers act on it, not just read it.

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