353 件（alirezarezvani のリポジトリ） ・ 人気順
概要と使いどころ
Automatic code quality and best practices analysis. Use proactively when files are modified, saved, or committed. Analyzes code style, patterns, potential bugs, and security basics. Triggers on file changes, git diff, code edits, quality mentions.
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。
Automatically suggest tests for new functions and components. Use when new code is written, functions added, or user mentions testing. Creates test scaffolding with Jest, Vitest, Pytest patterns. Triggers on new functions, components, test requests, testing mentions.
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 conventional commit messages automatically. Use when user runs git commit, stages changes, or asks for commit message help. Analyzes git diff to create clear, descriptive conventional commit messages. Triggers on git commit, staged changes, commit message requests.
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。
Auto-generate API documentation from code and comments. Use when API endpoints change, or user mentions API docs. Creates OpenAPI/Swagger specs from code. Triggers on API file changes, documentation requests, endpoint additions.
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。
Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store
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。
Verify every @path chain import and every markdown link inside every CLAUDE.md in this project resolves to an existing file. Read-only — returns broken links with file:line refs, never 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。
Analyzes, generates, and enhances CLAUDE.md files for any project type using best practices, modular architecture support, and tech stack customization. Use when setting up new projects, improving existing CLAUDE.md files, or establishing AI-assisted development 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。
Audit every CLAUDE.md in this project for drift against the last week of git history. Flags sections that reference deleted files, renamed paths, or removed dependencies. Read-only — returns a punch list, never 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。
Behavioral guardrails for LLM-assisted coding. Use when writing, reviewing, or refactoring code in any project to avoid overcomplication, keep changes surgical, surface assumptions early, and execute against verifiable success criteria.
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-detect this project's tech stack from package.json / requirements.txt / pyproject.toml / go.mod / Cargo.toml and diff it against the Tech Stack section of every CLAUDE.md. Read-only — returns added / removed / renamed dependencies, never 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。
Generate phased implementation roadmaps with Epic/Story/Task breakdown, effort estimates, and validation checkpoints. Use when cto-architect needs to create actionable technical roadmaps from architecture designs.
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 structured 8-section validation reports with verdict (GOOD/BAD/NEEDS MAJOR WORK), strengths, critical flaws, blindspots, and concrete path forward. Use after strategic-cto-mentor has completed validation analysis and needs to produce final deliverable.
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 incoming user requests to detect intent, request type (design/validate/debug/document), complexity level, and identify vague requirements or buzzwords that need clarification. Use when cto-orchestrator receives new requests that need classification before routing to specialist agents.
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。
Deep expertise in ML/CV model selection, training pipelines, and inference architecture. Use when designing machine learning systems, computer vision pipelines, or AI-powered features.
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。
Transform clarified user requests into structured delegation prompts optimized for specialist agents (cto-architect, strategic-cto-mentor, cv-ml-architect). Use after clarification is complete, before routing to specialist agents. Ensures agents receive complete context for effective work.
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。
Guidance for scaling systems from startup to enterprise scale. Use when planning for growth, diagnosing bottlenecks, or designing systems that need to handle 10x-1000x current load.
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。
Infrastructure and development cost estimation for technical projects. Use when planning budgets, evaluating build vs buy decisions, or projecting TCO for architecture choices.
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 targeted clarifying questions (2-3 max) that challenge vague requirements and extract missing context. Use after request-analyzer identifies clarification needs, before routing to specialist agents. Helps cto-orchestrator avoid delegating unclear requirements.
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。
Identify and challenge implicit assumptions in plans, proposals, and technical decisions. Use when strategic-cto-mentor needs to surface hidden assumptions and wishful thinking before they become costly mistakes.
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。
Recommend architecture patterns (monolith, microservices, serverless, modular monolith) based on scale, team size, and constraints. Use when cto-architect needs to select the right architectural approach for a new system or migration.
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。
Detect common technical and organizational anti-patterns in proposals, architectures, and plans. Use when strategic-cto-mentor needs to identify red flags before they become problems.
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。
Recommend technology stacks based on project requirements, team expertise, and constraints. Use when selecting frameworks, languages, databases, and infrastructure for new projects.
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 the user dumps a batch of inputs at once — a pile of emails, a backlog of Slack/Teams messages, a list of asks, meeting action items, a notes brain-dump — and needs it sorted into action. Classifies each item, assigns owner + next step + priority, and flags which need a full /structure brief or a /decide call. Trigger on "/triage", "triage this", "process my inbox", "sort these asks", "clear my backlog", "what do I do with all this".
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。
First-run guided setup for a fresh gAIOS clone. Interviews the user (identity, role, priorities, voice, connections, team, pain, guardrails) and fills the templates — CLAUDE.md, context/, references/voice.md, connections.md — then introduces the WAT / wiki / workflows / experiments features. Trigger on "/setup", "set me up", "get started", "onboard me", or a fresh clone where CLAUDE.md still has {{placeholders}}.
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。