プロジェクトで使う業務用語や概念の境界を、具体例とコードの照合で明確にします。決まった定義を用語集に記録し、重要な設計判断の理由も必要に応じて残すスキルです。
- 曖昧な業務用語を整理したいとき
- GLOSSARY.mdの作成・更新
- 業務上の定義とコードの整合確認
77 件 ・ 関連度順
概要と使いどころ
プロジェクトで使う業務用語や概念の境界を、具体例とコードの照合で明確にします。決まった定義を用語集に記録し、重要な設計判断の理由も必要に応じて残すスキルです。
画面の余白、文字、角丸、影、動きを見直し、見た目と操作感を整えるスキル。ボタンやカードなどの細部を点検し、変更前後が分かる具体的な改善案を示します。
OpenDesign's operating review: growth, burn, and the concrete path to sustainability without losing the open ethos. Built as a decision-grade corporate strategy deck for leadership team.
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。
Turns decided work — a PRD, design doc, RFC, or thread — into tasks a builder can act on without guessing. Finds slices that each prove something, grounds them in the code, and writes intent, observable criteria with concrete values, the boundary, what the change disturbs, and only the decisions that are hard to reverse. Walks every surface the work exposes and sweeps the nine unwritten requirements, recording each landing as a criterion already in the source, existing behaviour, n/a, or Unresolved — never as a criterion the walk invented. Defaults to one task per source. Use when the user says "write the task", "cut this PRD into tasks", "turn this design doc into work", or "tlc-plan". Do NOT use for discovery itself or to implement — a one-line ticket is a decision; a blank wish is not.
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。
Review or de-slop concrete changes in ccch1mneyyy/dsh-TUI at maintainer level: PR numbers or URLs, branches, commit ranges, patch files, staged or unstaged worktrees, and scoped repository-hygiene requests. Use for evidence-first correctness, contract, repository-rule, process, and behavior-preserving cleanup review, including debug residue, dead or duplicate code, speculative abstractions, stale comments or tests, and unrelated diff churn. Do not use for abstract designs with no concrete repository artifact; use audit for repository-wide assessments and vuln-check for security-only checks.
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。
Raw, anti-design aesthetic inspired by concrete architecture with unadorned elements, jarring layouts, and functional minimalism.
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 React interfaces with the full shadcn/ui catalog. The agent writes a brief, Jev picks components and a style recipe from bounded catalogs, then the agent implements, renders, and reviews against concrete checks.
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 the UX of custom-code Databricks Apps (AppKit/React) data screens — KPI/overview pages, reports, charts, tables, and Genie/chat data assistants — mapped to concrete AppKit components. Use when BUILDING or reviewing the UI of an AppKit/React app that displays data or answers data questions: choosing genre, layout, charts, KPIs, semantic color, required states (loading/empty/error), IBCS notation, and AI-result trust (showing generated SQL/sources for Genie/chat). A plain "create a dashboard" request means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, NOT this skill. Also NOT for non-data frontend (forms, settings, auth, marketing) or scaffolding/build/deploy (→ databricks-apps). Complements databricks-apps; use it alongside whenever a custom app has a chart, table, KPI, report, or Genie/chat/AI surface.
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。
Suede AI eval design and coverage audit: AI-SPEC, failure-mode rubric with severity scoring, concrete pass/fail eval cases, coverage and infrastructure scores, and mechanical acceptance gates. Use when a change ships LLM, RAG, agent, classifier, prompt, or generated-media behavior, or when asked to write evals for an AI feature, design test cases for a model surface, audit existing eval coverage, or judge whether AI behavior is safe to ship. No AI-SPEC means no eval plan, and no eval plan holds the recommended ship verdict. NOT FOR: reviewing or grading the implementation code behind the AI surface (use suede-code); wiring a passing suite into CI as a required check (use suede-ci-gate); UAT of the built feature beyond the eval suite (a private Suede Labs companion, not in this pack).
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。
Piaget's constructivism, schema theory, and cognitive development as practical tools for curriculum design. Covers assimilation, accommodation, equilibration, the four stages (sensorimotor, preoperational, concrete operational, formal operational), conservation tasks, schema-based reading and problem-solving, and the distinction between developmental readiness and domain-specific expertise. Use when designing age-appropriate material, diagnosing why a learner is not assimilating new content, or building on prior knowledge.
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。
Turn a rough feature, product interaction, or architecture idea into a concrete design. Use when meaningful decisions remain open; avoid for already-clear local edits.
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 a concrete technical proposal with evidence and tradeoffs when a decision needs design. No implementation or automatic reviewer.
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 deployment-focused distillation systems that balance model size, accuracy, calibration, and cascade escalation under real resource limits. Best for teacher-student compression, threshold design, and failure-aware deployment. Activate on "model compression", "teacher- student", "distillation score", "cascade model", "edge deployment", or "model calibration". NOT for generic deep-learning overviews, prompt optimization, or training work without a concrete distillation objective.
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。
What you can build and do with an always-on AI agent that has episodic memory. Covers concrete product ideas, workflows, emergent capabilities from persistence plus memory, and real-world examples of deployed persistent agents. Helps you go from "I have the architecture" to "here's what it actually does for me." Activate on: "what can an always-on agent do", "persistent agent use cases", "agent applications", "proactive agent ideas", "what to build with episodic memory", "always-on agent product", "personal AI assistant ideas", "/always-on-agent-applications". NOT for: building the architecture (use always-on-agent-architecture), designing inputs (use always-on-agent-inputs), safety and privacy (use always-on-agent-safety).
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, implement, and review web interface layout, component states, feedback, and motion within the current CodeConductor workflow. Use for concrete web UI work or requested UI audits, not backend-only tasks or native mobile apps.
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, implement, review, and audit Android Jetpack Compose UI/UX for phone interfaces. Use when a request concerns concrete Compose layout, components, interaction, accessibility, or visual behavior. Do not activate for framework or dependency presence alone; non-UI Android work is excluded.
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。
Redisを使ったキャッシュ、アクセス回数制限、複数処理の同時実行制御、メッセージ配信を設計し、キーの有効期限や接続管理も見直すスキル。
AIエージェントの成果物を、正確さ・網羅性・明瞭さ・実行しやすさ・簡潔さの5軸で自己評価し、根拠付きの点数と優先順位を付けた改善案をまとめます。
Evaluate and carry out non-trivial software-system changes from first principles. Use when assessing RFCs, issues, designs, features, refactors, migrations, dependency changes, or proposed fields, events, APIs, modules, and services whose need, consumers, system fit, validation, or rollback require scrutiny. Read the actual system, identify the concrete problem and named semantic consumers, choose the smallest sufficient solution, reject pseudo-requirements and speculative abstractions, and require evidence proportional to risk. Do not use for mechanical edits, source-code explanation, or a dedicated review of an already-complete diff.
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。
Read one supplied paper closely enough to reconstruct how its authors actually got there, rather than restating what the abstract claims. Use for 精读论文, 讲透这篇论文, 把这篇读懂, 作者为什么这么设计, 这个公式怎么推出来的, paper x-ray, and deep single-paper comprehension before building on, reviewing, presenting, or citing that paper. Recovers the real starting point and the bet the authors placed, separates load-bearing design from decoration, grounds each key formula in a worked micro-example with concrete numbers, and checks how far the evidence actually reaches, including where the authors are confident and where the paper does not report something. Delivers a structured Markdown long-read by default. Not a summary, not a translation, not a peer 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。
Design and plan end-to-end Azure IoT and Smart City solutions: requirements, architecture, security, operations, cost, and a phased delivery plan with concrete implementation artifacts.
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 a question, decision, plan, tradeoff, or claim needs a rigorous verdict and one perspective is not enough. Spawns a panel of 3 to 5 subagent jurors that form independent blind opinions, deliberate anonymously under an anti-anchoring and anti-sycophancy protocol, and return one committed verdict with confidence, preserved dissent, and a concrete next action. Domain-agnostic across engineering, architecture, data, product, hiring, strategy, vendor choice, build-vs-buy, and research design. Trigger phrases include "convene a jury", "have agents debate and decide", "get a panel to decide", "multi-agent decision", "stress-test this and decide", "monte um juri", "tribunal de agentes", "painel para decidir". Do NOT use to only critique without deciding (use the-fool for that), to build a plan or write the solution itself, or for simple factual lookups.
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。
Generate OpenEnv environments from a concrete use case (for example, "generate an env for the library textarena"). Use when asked to design or implement a new environment under envs/ by researching a target library/API, selecting matching OpenEnv examples, asking key implementation questions, and building models/client/server/openenv.yaml. Do not use for model training or evaluation tasks.
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。
Produces design reference imagery before implementation — screen concepts, layout directions, and flows for web or mobile that make a verbal brief concrete enough to argue with. Use this when a brief needs visualizing before anyone builds, when comparing layout directions, when handing a developer a target, or when stakeholders are describing different things with the same words.
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。