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。
System architecture design and review. Use when designing architecture, evaluating microservices vs monolith, writing ADRs, choosing a database, planning for scalability, reviewing system design, or generating architecture diagrams.
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。
Architecture design and analysis tools for making informed technical decisions: visualize system structure, analyze dependencies and coupling, detect architectural patterns, and run decision workflows for databases, patterns, and monolith-vs-microservices trade-offs.
Before generating diagrams or an assessment, confirm these inputs. If any is unknown or vague, ASK — do not assume:
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 |
|---|---|---|
architecture_diagram_generator.py | Generate component/layer/deployment diagrams from project structure | python scripts/architecture_diagram_generator.py ./project --format mermaid --type component |
dependency_analyzer.py | Score coupling and find circular dependencies across package managers | python scripts/dependency_analyzer.py ./project --output json --check circular |
project_architect.py | Detect architecture pattern, layer violations, and code smells | python scripts/project_architect.py ./project --check layers --verbose |
Run any script with --help for full flags.
Load the reference that matches the task — keep this file lean and pull detail on demand:
Covers: system-level architecture analysis (pattern detection, layer validation, component diagramming) for existing codebases; technology-agnostic dependency analysis across npm, pip, Poetry, Go modules, and Cargo; architecture decision workflows (database, pattern, monolith-vs-microservices); diagram generation in Mermaid, PlantUML, and ASCII.
Does NOT cover:
senior-devops (capacity planning) and senior-qa (performance test harnesses).senior-security or senior-secops for CVE/SAST/DAST.senior-frontend and design-auditor.senior-devops and release-orchestrator.| Skill | Integration | Data Flow |
|---|---|---|
senior-backend | Architecture patterns inform backend service boundaries and API contract design | Architect assessment output (detected pattern, layer assignments) feeds into backend module scaffolding |
senior-devops | Deployment diagrams and technology detection drive infrastructure-as-code decisions | Deployment diagram type output + detected technologies list consumed by DevOps for Terraform/K8s config |
senior-security | Dependency analysis surfaces packages that need security review | Dependency list JSON (--output json) passed to security scanning for CVE correlation |
senior-fullstack | Architecture pattern selection determines which fullstack scaffold template to use | Pattern selection workflow result (e.g., modular monolith) maps to project_scaffolder.py --type flag |
code-reviewer | Layer violation and god-class findings become review checklist items | project_architect.py --output json issues array integrated into code review checklists |
tech-stack-evaluator | Technology detection results feed tech stack evaluation for upgrade/migration decisions | Detected technologies list and dependency versions inform stack evaluation decision matrices |
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 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。
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。
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。