「sci」の検索結果

Author and own ONE content type's typed schema (the CONTENT-TYPE.md) at .unikit/gamedesign/content-types/CT-<slug>.md — the content / catalog layer of the GDD (cards, items, weapons, enemies, levels, quests, loot). Use whenever the user wants to ADD a new kind of content or UPDATE its schema, e.g. "add a new content type", "design the loot content", "define the card schema", "add an enemies content type", "add a rarity field to items", "switch this catalog to curated". Create the skeleton, fill its typed field schema (CT.fields), scale, relationships, and validation, AND revise the schema under the delta discipline (a schema change bumps the version + changelog). Selects the scale (bulk | curated) and self-registers content_types/content. This owns the content SCHEMA, not the catalog of values — adding individual entries/units is data handled in the editor, not a schema edit. To add or detail a system use /unikit-gd-system; to add a flow use /unikit-gd-flow; to apply a multi-zone edit use /unikit-gd-apply.

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。

Author and own one flow's design document (the FLOW.md objective flow) at .unikit/gamedesign/flows/FLOW-<slug>.md — the dynamics layer of the GDD (what the player does over time). Create the skeleton and walk the collaborative section-cycle to write its objectives, pacing, dependencies, and funnel events ("design the first-session flow", "map the onboarding sequence", "write the FLOW for the boss encounter"), AND revise it after approval under the delta discipline ("retune the pacing", "add a branch", "change a GOAL", "rework the onboarding") — a cue/number change is Tuning, a small step change a Tweak, restructuring a Rework; each bumps the version and logs the delta. Selects the wiring mode (linear | conditional | emergent) and re-renders the ## Flow Map [gen] / ## Funnel [gen] blocks in GAME.md. To add or detail a system use /unikit-gd-system; to edit GAME.md content use /unikit-gd-spec; to apply a multi-zone edit use /unikit-gd-apply; for a new game concept use /unikit-gd-brainstorm.

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。

Land a ready branch - push, PR, pinned CI watch, squash-merge, issue verification, cleanup. Use for every PR landing; encodes the run-ID pinning and cleanup discipline.

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。

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature.

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。

Unified verification engine for Python data science projects. Covers environment checks, type checking, linting, tests, security scans, code review with DS anti-patterns, and notebook checks. Commands (/verify, /quality-gate) invoke different subsets of this skill.

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。

Apply these opinionated testing conventions whenever writing, reviewing, or planning tests: what earns a test and what is coverage theatre, asserting outputs rather than mock calls, the three modes (functional, performance, security), naming and isolation rules, where to mock, and reporting findings for coverage rather than self-filtering. Includes house Jest standards for NestJS unit and contract tests, TDD discipline, and test-report structure.

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。

Use this skill to execute AetherLang V3 AI workflows from Claude Code. AetherLang provides 9 specialized AI engines for culinary consulting, business strategy, scientific research, and more.

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。

Refine academic writing for computer science research papers targeting top-tier venues (NeurIPS, ICLR, ICML, AAAI, IJCAI, ACL, EMNLP, NAACL, CVPR, WWW, KDD, SIGIR, CIKM, and similar). Use this skill whenever a user asks to improve, polish, refine, edit, or proofread academic or research writing — including paper drafts, abstracts, introductions, related work sections, methodology descriptions, experiment write-ups, or conclusion sections. Also trigger when users paste LaTeX content and ask for writing help, mention "camera-ready", "rebuttal", "paper revision", or reference any academic venue or conference. This skill handles both full paper refinement and section-by-section editing.

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。

Create clear architecture views of Azure resources and their relationships. Use this skill when users ask for diagrams, topology summaries, dependency maps, or deployment overviews. Generates Mermaid, ASCII, and structured documentation for architecture review and compliance.

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。

Implement randomization methods for RCTs. Use when user mentions: random assignment, treatment allocation, stratification, blocking, permutation randomization, cluster randomization, randomization balance, misfit handling, re-randomization.

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。

Analyze data from randomized controlled trials. Use when user mentions: treatment effects, ITT analysis, LATE, TOT, compliance analysis, attrition, balance checks, heterogeneous effects, RCT results, experimental analysis.

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。

Handle ethical requirements, IRB approval, trial registration, and pre-analysis plans for RCTs. Use when user mentions: research ethics, IRB, informed consent, trial registration, pre-analysis plan, PAP, data security, vulnerable populations, research transparency.

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。

Summary statistics, data exploration, and descriptive analysis. Use for: summary stats, describe data, data exploration, distributions, means, medians, correlations, cross-tabs.

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。

Causal inference with treatment/control groups over time. Use when user mentions: treatment effects, policy evaluation, pre/post comparison, parallel trends, DID, DiD, difference in differences, natural experiment, quasi-experimental.

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。

Design randomized controlled trials for causal inference. Use when user mentions: randomized evaluation, RCT, field experiment, randomized experiment, treatment assignment, causal impact, experimental design, control group, intervention evaluation.

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。

Publication-quality statistical visualization with mandatory best practices. Use when creating plots, charts, figures, or any data visualization. Enforces accessibility, uncertainty display, proper labeling, and statistical accuracy.

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。

Core statistical methodology and pedagogical approach for all Inquiro analyses. Always loaded to maintain teaching quality and reproducibility standards.

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。

Calculate statistical power and sample sizes for RCTs. Use when user mentions: power analysis, sample size calculation, minimum detectable effect, MDE, statistical power, effect size, clustering effects, design effect, ICC, intra-cluster correlation.

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。

Comprehensive regression model diagnostics and assumption checking. Use when validating regression models, checking assumptions (linearity, homoskedasticity, normality, independence), detecting outliers/influence, testing multicollinearity, or when user mentions residuals, heteroskedasticity, VIF, Cook's distance, or diagnostic plots.

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。

PRD 到 UI 线框 / 结构阶段：当需要把 PRD 的界面定义先转成 screen inventory、状态模型、ASCII 布局、低保真 HTML mockup， 并先确认结构/状态而不是视觉 polish 时使用。这个 Skill 只负责 UI mockup 的结构阶段；如果用户要高保真、真实前端项目对齐、 project-native preview、component map、implementation notes 或“开发完全复刻”，必须转用 ui-mockup-desktop-workbench。

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。

PRD 到高保真 UI 交付对齐 / 桌面工作台 UI mockup：当用户已有 PRD、UI 规范、真实前端项目路径、截图或页面状态清单， 需要先从 PRD 提炼 UI 结构、状态模型和 ASCII 布局，再进入高保真 mockup、项目原生 preview 或开发交付 handoff 时使用。 优先输出项目原生 preview route/component；只有早期概念确认或无法接入真实项目时才输出 standalone HTML。 必须包含结构阶段产物、screen contract、component map、implementation notes、截图/验证结果和 HTML/preview 的迁移边界。

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。

Evaluate an incoming workflow upgrade — a skill, MCP server, subagent, library, external service, prompt, or pattern — through one disciplined pipeline before adopting it. Security is a blocking gate. Records every verdict so the same thing is never evaluated twice. Use when considering a new tool from a post, repo, or recommendation. Triggers — "vet this", "should we adopt", "is this safe to install", "evaluate this skill/MCP", "what do you think of this tool".

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。

Deliberate system-improvement loop — audit your own Claude Code setup (rules / memory / skills / MCP / agents / registry), evaluate incoming tools via /vet, adopt the worthwhile ones with discipline (backup → verify), and record every decision. Use when bringing in a tool/idea/collection to improve the setup, or when doing a tooling-improvement pass. Triggers — "upgrade the workflow", "audit our setup", "let's improve the tooling", "evaluate this for us", when handed a post/repo/reel with a tool.

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。

Use when generating visual artifacts — explanations, diagrams, slides, or diff visualizations. Triggers on "explain X visually", "diagram this", "show as slides", "diff against main". NOT for rendering a plan as HTML (see mk:visual-plan), live media generation (see mk:multimodal), browser QA (see mk:qa), or plan critique (see mk:plan-ceo-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。