AUTO-EXECUTE import of external work items (GitHub/JIRA/ADO) since last import. NO PROMPTS - immediately runs with defaults. Creates READ-ONLY references in living docs. Options available but NOT required.
Skills（SKILL.md）は、AIエージェント（Claude Code、Cursor、Codexなど）に特定の能力を追加するための設定ファイルです。
詳しく見る →AUTO-EXECUTE import of external work items (GitHub/JIRA/ADO) since last import. NO PROMPTS - immediately runs with defaults. Creates READ-ONLY references in living docs. Options available but NOT required.
Analyzes conversation history to improve CLAUDE.md files. Use when you notice patterns in how Claude misunderstands requests, want to consolidate repeated guidance, or improve instruction clarity based on actual usage.
Improve skill(s) by analyzing the current session.
Systematically work through TBTA features using the 6-stage STAGES.md workflow. Use when user wants to improve TBTA features, work on TBTA, or continue TBTA feature work.
Expert at automatically applying improvements to Claude Code components based on quality analysis. Enhances descriptions, optimizes tool permissions, strengthens security, and improves usability. Works in conjunction with analyzing-component-quality skill.
Enabling monetization through virtual goods and currencies with virtual economy design, store implementation, payment integration, and purchase validation for gaming applications.
Manage Gmail inbox with AI-powered triage, cleanup, and restore. Use when the user mentions inbox, email triage, clean inbox, email cleanup, check email, email summary, delete emails, manage inbox, or wants to organize their email.
Expert guidance for building and maintaining the Para Obsidian inbox processing system - a security-hardened automation framework for processing PDFs and attachments with AI-powered metadata extraction. Use when building inbox processors, implementing security patterns (TOCTOU, command injection prevention, atomic writes), designing interactive CLIs with suggestion workflows, integrating LLM detection, implementing idempotency with SHA256 registries, or working with the para-obsidian inbox codebase. Covers engine/interface separation, suggestion-based architecture, confidence scoring, error taxonomy, structured logging, and testing patterns. Useful when user mentions inbox automation, PDF processing, document classification, security-hardened file processing, or interactive CLI design.
Workflow for processing large Things3 inboxes (100+ items) using LLM-driven confidence matching and intelligent automation. Integrates with personal taxonomy and MCP tools for efficient cleanup with self-improving pattern learning.
Handle production incidents effectively. Use when responding to outages, conducting post-mortems, or improving reliability. Covers incident response and blameless culture.
Create post-incident timeline and actions.
インシデント調査で根本原因を特定するためのなぜなぜ分析ファシリテーションツールです。推測を避け、ユーザーの発言を記録し、リアルタイムでマインドツリーを作成して全体を可視化します。複合要因を分割し、最低1つの根本原因を特定します。
Create and execute incident response procedures for security breaches, data leaks, and cyber attacks. Use when handling security incidents, creating response playbooks, or conducting forensic analysis.
Comprehensive incident root cause analysis skill for distributed systems. Analyzes logs, metrics, and traces to identify cascading failures, resource contention, and root causes through systematic anomaly detection, timeline correlation, and evidence-based hypothesis testing.
Create actionable runbooks for common incidents.
Rapid incident classification, severity assessment, and response coordination. Use when relevant to the task.
incident-handling
Use when writing code, documentation, or comments - always use accessible and respectful terminology
Generate culturally diverse names for examples, mock data, and test fixtures. Includes edge-case names that catch bugs.
AI-powered quality assessment using LLM-as-Judge pattern with BMAD risk scoring and formal gate decisions. Use for evaluating increment specs, assessing task completeness, or making quality gate decisions (PASS/CONCERNS/FAIL). Chain-of-thought reasoning ensures transparent evaluation.
Use when building multi-day features, avoiding long-lived branches, features taking >1 day, changes touching multiple systems, or high-risk changes needing gradual rollout - break features into deployable increments that each provide value
Use when implementing features or refactoring with TDD - enforces writing ONE test at a time, implementing minimal code to pass, then repeating, preventing batch test writing that defeats incremental design discovery
Generate hierarchical AGENTS.md knowledge base for a codebase. Creates root + complexity-scored subdirectory documentation.
indigenous-leader-analyst
Deep domain research and expertise synthesis across industries, combining academic research, market intelligence, and practitioner knowledge
Systematic research protocol for discovering novel AI-native software businesses in the synthetic workforce era. Maps capability trajectories, analyzes segment-problem spaces, generates business models, and calculates inevitability scores across 3-24 month time horizons. Use when exploring AI business opportunities, conducting market research, or identifying automation-native ventures.
Find and evaluate influencers for marketing partnerships
Эксперт по influencer-маркетингу. Используй для работы с инфлюенсерами, UGC и creator partnerships.
infra-adoption
infra-architect
infra-debugger
infra-deployer
Comprehensive infrastructure engineering covering DevOps, cloud platforms, FinOps, and DevSecOps. Platforms: AWS (EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation), Azure basics, Cloudflare (Workers, R2, D1, Pages), GCP (GKE, Cloud Run, Cloud Storage), Docker, Kubernetes. Capabilities: CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins), GitOps, infrastructure as code (Terraform, CloudFormation), container orchestration, cost optimization, security scanning, vulnerability management, secrets management, compliance (SOC2, HIPAA). Actions: deploy, configure, manage, scale, monitor, secure, optimize cloud infrastructure. Keywords: AWS, EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation, Azure, Kubernetes, k8s, Docker, Terraform, CI/CD, GitHub Actions, GitLab CI, Jenkins, ArgoCD, Flux, cost optimization, FinOps, reserved instances, spot instances, security scanning, SAST, DAST, vulnerability management, secrets management, Vault, compliance, monitoring, observability. Use when: deploying to AWS/Azure/GCP/Cloudflare, setting up CI/CD pipelines, implementing GitOps workflows, managing Kubernetes clusters, optimizing cloud costs, implementing security best practices, managing infrastructure as code, container orchestration, compliance requirements, cost analysis and optimization.
Safely destroy infrastructure with state backup and verification
Enforces Terraform best practices for safe and scalable infrastructure as code. Emphasizes modularity, state management, and security. Automatically applied for IaC implementation.
infra-tester
Terraform/Docker Composeによるインフラ構築のワークフロー、ベストプラクティス、Well-Architected Framework対応を定義
Create Terraform/Pulumi/CloudFormation for multi-cloud.
Expert guide for documenting infrastructure including architecture diagrams, runbooks, system documentation, and operational procedures. Use when creating technical documentation for systems and deployments.
Infrastructure, DevOps, and platform reliability
Infrastructure guidelines for A4C-AppSuite. Covers idempotent Supabase SQL migrations with RLS policies, Kubernetes deployments for Temporal workers, CQRS projections with PostgreSQL triggers, and AsyncAPI contract-first event design. Emphasizes safety, idempotency, and SQL-first development.
Manage network hosts and devices across all UniFi sites. Monitor host status, device configuration, and infrastructure health for comprehensive inventory management.
Transform infrastructure documentation, runbooks, and operational knowledge into reusable Claude Code skills. Convert Proxmox configs, Docker setups, Kubernetes deployments, and cloud infrastructure patterns into structured, actionable skills.
Use when working with Terraform (.tf, .tfvars), Ansible (playbooks, roles, inventory), Docker (Dockerfile, docker-compose.yml), CloudFormation, or any infrastructure-as-code files — provides validation workflows, tool chains, and common mistake prevention
Generate $HOME/.claude/CLAUDE.md with AI-driven environment detection and advanced configuration options
Creates AI agent task management structure with feature backlog (ai/tasks/), TDD enforcement, and progress tracking. Use when setting up agent-foreman, initializing feature-driven development, creating task backlog, or enabling TDD mode. Triggers on 'init harness', 'setup feature tracking', 'create feature backlog', 'enable strict TDD', 'initialize agent-foreman'.
Use to create complete architecture documentation structure. Creates all required architecture documents from templates.
Initialize complete governance framework in a project - creates constitution, roadmap, directory READMEs, and issue/spec templates with guided setup process
Use to set up Obsidian vault and populate it with existing codebase knowledge. Enables context memory for AI development.
initialize-repository