This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
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。
Manage and optimize monorepos with Turborepo, Nx, pnpm workspaces, and Changesets. Use when working in monorepos, running impact analysis, optimizing build times with remote caching, migrating from multi-repo, or coordinating publishing.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Navigate, manage, and optimize monorepos at any scale. Covers Turborepo, Nx, pnpm workspaces, and Lerna/Changesets for cross-package impact analysis, selective builds on affected packages only, dependency graph visualization, remote caching configuration, migration from multi-repo to monorepo with preserved git history, and coordinated package publishing with automated changelogs.
Keywords: monorepo, Turborepo, Nx, pnpm workspaces, Changesets, dependency graph, remote cache, affected packages, selective builds, cross-package impact, npm publishing, workspace protocol
workspace:* replacement during publish.Before analyzing or configuring, confirm these inputs. If any is unknown or vague, ASK — do not assume:
dependency_graph.py vs impact_detector.py vs package_analyzer.py)--ref and what counts as changed)Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
| Tool | Purpose | Command |
|---|---|---|
dependency_graph.py | Generate a Mermaid dependency graph of internal packages | python scripts/dependency_graph.py . --focus @repo/ui --direction dependents |
impact_detector.py | Detect which packages are affected by file changes | python scripts/impact_detector.py . --ref origin/main --affected-only |
package_analyzer.py | Analyze package structure, dependencies, and health | python scripts/package_analyzer.py . --only-shared |
Load the reference that matches the task — keep this file lean and pull detail on demand:
This skill covers:
This skill does NOT cover:
performance-profilerci-cd-pipeline-builderrelease-managerdependency-auditor| Skill | Integration | Data Flow |
|---|---|---|
ci-cd-pipeline-builder | Monorepo-aware CI workflows use --filter flags and remote caching tokens | Monorepo Navigator defines filter patterns and cache config that CI pipelines consume |
release-manager | Changesets versioning feeds into release orchestration and tag management | Release Manager triggers changeset version and changeset publish as part of release flow |
dependency-auditor | Workspace dependency graph informs vulnerability and license scanning scope | Monorepo Navigator exports the package dependency tree that Dependency Auditor analyzes |
performance-profiler | Build profiling data identifies slow packages for optimization | Performance Profiler measures per-package build times surfaced by Turborepo --summarize |
changelog-generator | Changesets produce per-package changelogs consumed by release notes | Changeset summaries flow into Changelog Generator for formatted release documentation |
tech-debt-tracker | Cross-package coupling and circular dependencies surface as tracked tech debt items | Monorepo Navigator's impact analysis identifies coupling hotspots that Tech Debt Tracker records |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
This skill should be used when the user asks to "check accessibility", "audit WCAG compliance", "scan HTML for a11y issues", "check color contrast", or "find accessibility violations in web pages".
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 run statistically rigorous A/B tests and experiments. Use when planning experiments, calculating sample sizes, designing test variants, selecting metrics, analyzing results, or when someone says "let's test that."
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 analyze A/B tests: sample size, test duration, and statistical significance for conversion experiments. Use when setting up an A/B test, calculating sample size, designing an experiment, or analyzing results.
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。
Sales execution across pipeline, discovery, demos, negotiation, and closing. Use when qualifying opportunities, running MEDDIC discovery, building account plans, handling objections, structuring proposals, or forecasting pipeline.
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 ad creative across Google, Meta, LinkedIn, Twitter/X, and TikTok with platform format specs, headline formulas, and A/B testing. Use when writing ad copy, generating headline variations, creating ad sets, or validating creative.
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。
Answer Engine Optimization (AEO): optimize content to be cited by LLMs (ChatGPT, Claude, Perplexity, Gemini) in their answers. Use when designing content for LLM citation, auditing citability, or structuring Q&A schema.
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。