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「present」の検索結果

1,257 件 ・ 関連度順

概要と使いどころ

PAO workflow for scanning, drafting, and presenting community responses with human review gate

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。

github/gh-aw5,3952026年10月14日 更新

squad

無料

Squad's command catalog and interactive menu. Invoke via /squad (slash command) or natural language ("squad commands", "what can squad do", "show me squad options"). Presents categorized operations (Install & Upgrade, Team Management, Issues & PRs, Plugins & Skills, Model & Cost, Sessions & State) as an interactive picker. Routes to the right squad CLI command or the Squad coordinator agent.

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。

github/gh-aw5,3952026年10月14日 更新

Transform text content into professional Mermaid diagrams for presentations and documentation. Use when users ask to visualize concepts, create flowcharts, or make diagrams from text. Supports process flows, system architectures, comparisons, mindmaps, and more with built-in syntax error prevention.

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。

breferrari/obsidian-mind5,3102026年10月14日 更新

Shape pitches, brand stories, presentations, and creative writing with narrative frameworks such as the Hero's Journey, Story Spine, and Freytag's Pyramid. Use when a user wants to structure, critique, or strengthen a story.

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。

iflytek/skillhub5,2062026年10月14日 更新

Chinese-first academic Word and PowerPoint workflow for paper reading reports, thesis or group-meeting PPTs, editable DOCX/PPTX generation, Office file inspection, template matching, speaker notes, and layout quality checks. Use when the user asks to read papers into Word reports, create or polish PPT/PPTX, convert paper/thesis materials into slides, edit DOCX/PPTX, inspect Office files, or produce Chinese academic presentation/report deliverables. Preserve English paper titles, formulas, variable names, software commands, and references.

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。

zLanqing/codex-claude-academic-skills4,8912026年5月14日 更新

scgpt

無料

Embed and annotate single-cell expression data with scGPT, a foundation model for single-cell biology. Use this skill when: (1) Producing cell embeddings from an AnnData for clustering/integration, (2) Zero-shot or fine-tuned cell-type annotation, (3) Gene-level representation for perturbation/GRN tasks. For probabilistic single-cell models (scVI etc.), use the scvi-tools library.

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。

aipoch/open-science4,8502026年10月14日 更新

Generate Beamer presentations for the sewage-house-prices project by dispatching the Storyteller agent (creator) and Discussant agent (critic). Supports 4 formats — job market, seminar, short, lightning. Derives all content from the paper.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

a1

無料

VS-Enhanced Research Question Refiner - Prevents Mode Collapse and derives differentiated research questions Enhanced VS 3-Phase process: Modal question avoidance, alternatives presentation, differentiated RQ recommendation Use when: refining research ideas, formulating research questions, clarifying scope Triggers: research question, 연구 질문, PICO, SPIDER, research idea

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

a2

無料

VS-Enhanced Theoretical Framework Architect with Critique & Visualization Full VS 5-Phase process: Modal theory avoidance, Long-tail exploration, differentiated framework presentation Absorbed A3 (Devil's Advocate) critique and A6 (Conceptual Framework Visualizer) capabilities Use when: building theoretical foundations, designing conceptual models, deriving hypotheses, critiquing frameworks, visualizing models Triggers: theoretical framework, 이론적 프레임워크, conceptual model, 개념적 모형, hypothesis derivation, critique, devil's advocate, 반론, visualization, diagram

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

b1

無料

VS-Enhanced Literature Review Strategist - Comprehensive support for multiple review methodologies Full VS 5-Phase process: Prevents Mode Collapse and presents creative search strategies Supports: Systematic Review (PRISMA 2020), Scoping Review (JBI/PRISMA-ScR), Meta-Synthesis, Realist Synthesis, Narrative Review, Rapid Review Use when: conducting any type of literature review, systematic reviews, meta-analyses, scoping reviews, finding prior research Triggers: literature review, PRISMA, systematic review, scoping review, meta-synthesis, realist synthesis, narrative review, rapid review

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

Assesses a research paper outline (.qmd file) against structured criteria from Kosuke Imai's empirical research guide. Evaluates the abstract and section outline for: research question clarity, stated contributions, hypotheses and testable implications, data description, planned results and inferential approach, and robustness checks. Detects causal papers from the abstract and conditionally assesses identification strategy only when causal framing is present. Produces a structured markdown report with PASS/PARTIAL/FAIL assessments and actionable suggestions. Use when asked to assess, evaluate, review, or check a paper outline, abstract-and-outline, or research plan in a .qmd file.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

referee2

無料

Systematic audit and review by Referee 2. Two modes — "deck" reviews slide presentations for rhetoric, visual quality, and compile cleanliness; "code" performs cross-language replication and econometric audit of empirical pipelines. Use when reviewing slides, auditing code, or verifying replication.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

causal-ml

無料

This skill covers causal machine learning methods in applied economics and quantitative social science. Use when implementing or choosing between modern ML-based causal estimators — including double machine learning, DML, partially linear models, interactive regression models, cross-fitting, Neyman orthogonality, debiased ML, causal forests, generalized random forest, GRF, honest causal trees, AIPW with machine learning, doubly robust with machine learning, DR-Learner, T-Learner, S-Learner, X-Learner, meta-learners, heterogeneous treatment effects, conditional average treatment effect, CATE, HTE, high-dimensional controls, LASSO controls, post-LASSO, post-double selection, Belloni-Chernozhukov-Hansen, Riesz representer, Chernozhukov, sample splitting, econml, DoubleML package, or any combination of machine learning and causal inference.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

Expert economics paper writing assistant synthesizing advice from 50+ top guides by Cochrane, McCloskey, Shapiro, Head, Bellemare, Goldin, Glaeser, Kremer, and other leading economists. USE THIS SKILL whenever the user writes, edits, reviews, rewrites, or structures any economics paper, thesis, job market paper, abstract, introduction, conclusion, results section, literature review, or referee response. Also handles LaTeX formatting, presentations, and paper audits. Covers all paper types (applied, theory, structural, mixed) and all sections.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

Guide for writing the introduction to an academic economics paper. Use this skill whenever the user asks for help writing, drafting, revising, or structuring an introduction to an economics paper - whether empirical micro, development economics, applied economics, or related fields. Also trigger when the user mentions "intro," "introduction section," "opening paragraphs," or asks how to motivate, frame, or present their research question in a paper. This skill synthesizes best practices from David Evans (CGDev), Keith Head, Claudia Sahm, Marc Bellemare, and Deirdre McCloskey.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

Audit economic analysis outputs (fiscal briefings, macro briefings, market research, longlists, and other quantitative economic documents) against methodology standards, academic literature, and common errors. Runs structured checks across core categories including counterfactual, additionality, discounting, double counting, distributional analysis, Aqua Book RIGOUR, and Flyvbjerg-style strategic misrepresentation detection. Returns a RAG scorecard with issues ranked by severity.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

Generate professional slide deck images from academic papers and content. Creates comprehensive outlines with style instructions, auto-detects figures from PDFs, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", or "slide deck" for papers.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

Opinionated Bayesian modeling workflow with PyMC and ArviZ. Contains critical guardrails (nutpie sampler, prior/posterior predictive checks, LOO-PIT calibration, prior sensitivity checks, 94% HDI, non-centered parameterizations, reproducible seeds) that agents won't apply unprompted — always consult before writing Bayesian model code. Trigger on: building probabilistic/Bayesian models, prior elicitation, MCMC inference, convergence diagnostics (divergences, R-hat, ESS), model comparison (LOO-CV, ELPD, stacking weights), hierarchical/multilevel models, count regressions, logistic regression with uncertainty, prior sensitivity analysis, reporting Bayesian results, or mentions of PyMC, ArviZ, InferenceData, credible intervals, posterior distributions, shrinkage, uncertainty quantification. Also trigger for model comparison, diagnosing sampling problems, choosing priors, or presenting stats to non-technical audiences.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.

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。

brycewang-stanford/Auto-Empirical-Research-Skills4,6252026年10月12日 更新

Find a specific GameObject in the opened Prefab (preferred when present) or the active Scene. Optionally include editable data, components preview, bounds, and limited hierarchy. Supports token-saving path-scoped reads via `paths` or `viewQuery`.

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。

IvanMurzak/Unity-MCP4,4482026年10月13日 更新

Create polished design artifacts as self-contained HTML: UI mockups, interactive prototypes, wireframes, landing pages, dashboards, app screens, mobile apps, slide decks (a.k.a. PPT / PowerPoint presentations), documents and résumés, animations, 3D objects, research reports, HTML email, diagrams, fliers, and visual explorations. Use whenever the user asks to design, mock up, prototype, wireframe, visualize, explore, or make a PPT/deck for an interface, product screen, user flow, content layout, visual artifact, or pitch/deck concept, even if they do not say "design". Also use to export a deck built with this skill to PowerPoint (PPT/PPTX) — but only decks authored here (deck-stage / this skill's slide-structured HTML), NOT arbitrary HTML, so confirm the target is such a deck first. Also use for setting up, importing, or authoring reusable design systems, UI kits, brand tokens, or component libraries. Harness-agnostic for Claude Code, Cursor, Codex Agent, and similar file-capable agents.

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。

JimLiu/baoyu-design4,3782026年9月23日 更新

Update Plugin Guide cards, fixtures, and annotations when public SDK contracts or Guide presentation change.

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。

get-bb/bb4,2932026年10月14日 更新

Present options with trade-offs for informed decision-making — use when choosing between approaches

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。

nyldn/claude-octopus4,2272026年10月14日 更新

Generate slide deck presentations from briefs — use when you need slides, pitch decks, or visual summaries

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。

nyldn/claude-octopus4,2272026年10月14日 更新