「fact」の検索結果

Expert-level green chemistry knowledge. Use when working with sustainable synthesis, atom economy, solvent selection, catalysis, renewable feedstocks, waste reduction, life cycle assessment, or the 12 principles of green chemistry. Also use when the user mentions 'atom economy', 'E-factor', 'green solvent', 'catalysis', 'renewable feedstock', 'waste minimization', 'sustainable chemistry', 'life cycle assessment', 'PMI', 'solvent selection guide', or 'benign by design'.

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。

Expert-level number theory knowledge. Use when working with divisibility, prime numbers, modular arithmetic, congruences, Diophantine equations, cryptography, quadratic residues, or analytic number theory. Also use when the user mentions 'prime', 'divisibility', 'modular arithmetic', 'congruence', 'GCD', 'Euler totient', 'Fermat little theorem', 'Chinese remainder theorem', 'quadratic residue', 'Diophantine equation', 'RSA', or 'prime factorization'.

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。

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

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 distinctive, production-grade frontend interfaces with high design quality. Generates creative, polished code that avoids generic AI aesthetics. Use when the user asks to build web components, pages, artifacts, posters, or applications, or when any design skill requires project context. Call with 'craft' to run the full shape-then-build flow, or 'teach' for design context setup.

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。

Extract and consolidate reusable components, design tokens, and patterns into your design system. Identifies opportunities for systematic reuse and enriches your component library. Use when the user asks to create components, refactor repeated UI patterns, build a design system, or extract tokens.

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。

Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background 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。

Generate an actionable, dependency-ordered tasks.md for the feature based on available design 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。

Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design 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。

Execute the implementation planning workflow using the plan template to generate design 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。

Stress-tests a fuzzy or vague feature idea before any PRD, spec, or ticket is written. TRIGGER when: the user has a fuzzy feature idea — one or two paragraphs, vague on users / scope / success — and wants to harden it, or says "grill / stress-test / pressure-test this idea." DO NOT TRIGGER when: the idea is already turned into a spec or PRD; bug fixes or refactors; the idea is hardened and you are ready to write the PRD → creating-prd.

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。

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

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。

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

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 an actionable, dependency-ordered tasks.md for the feature based on available design 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。

Execute the implementation planning workflow using the plan template to generate design 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。

Convert existing tasks into actionable, dependency-ordered GitHub issues for the feature based on available design 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。

React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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。

Write what the work found into the project's knowledge record, so the next session inherits it instead of re-deriving it. Use the moment something worth keeping exists: a fact taken from a source, a rule worked out, a decision or conclusion, a measurement, a correction to a recorded value, or a question left open - and check for unrecorded findings before implementation, handoff (including a PR), or finishing work. Record within the user's write authorization. The first write creates GROUNDING.yaml. Covers one-report update, add, set, review, same and distinct, judgments with a falsifier, and background capture.

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。

Set up kpopper watch for background branch compatibility, scoped shared facts, and daily review. Use when asked to watch a project's graph, check worktree changes against main, share external observations, or install a kpopper routine. Ordinary followup capture recommends scheduling without enabling it.

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。

Domain-Driven Design system for software development. Use when designing new systems with DDD principles, refactoring existing codebases toward DDD, generating code scaffolding (entities, aggregates, repositories, domain events), facilitating Event Storming sessions, creating bounded context maps, or performing code reviews with a DDD lens. Covers both strategic design (bounded contexts, subdomains, context maps, ubiquitous language) and tactical design (entities, value objects, aggregates, domain services, repositories). Supports all major architecture patterns (Hexagonal/Ports & Adapters, CQRS, Event Sourcing, Clean Architecture) with language-agnostic guidance and concrete examples in Python and TypeScript.

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。

Builds and improves task-specific decision artifacts from application requirements and labeled records. Use for data assembly, primitive and base-model selection, fitting, export/reload, inference policy, or bounded data/model/program improvement. Includes rules and no-training outcomes; does not require a rung ladder or training a general Jev.

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。

Creates complete newsletter editions for the Flow Factor Newsletter on Beehiiv. Generates full newsletter text (1,200-1,500 words), SEO metadata, subject lines, header illustration prompts, and NotebookLM audio briefing prompts. Use when user asks to write a newsletter, create email content, plan newsletter editions, or produce Beehiiv-ready content.

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 you need CRAP score and coverage risk analysis to find high-risk code before refactoring or release. Keywords: CRAP score, risk hotspots, cyclomatic complexity, test coverage gaps, coverage threshold.

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。

Re-audit code changes to identify side effects, regression risks, and unhandled edge cases before merging or deploying. Use after a change is complete and before merging to a shared branch, before deploying a hotfix, after complex multi-module refactoring, or when a previous review may have missed side effects in async, state-mutating, or security-sensitive code paths.

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。