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概要と使いどころ
Expert Terraform/OpenTofu specialist mastering advanced IaC automation, state management, and enterprise infrastructure patterns. Handles complex module design, multi-cloud deployments, GitOps workflows, policy as code, and CI/CD integration. Covers migration strategies, security best practices, and modern IaC ecosystems. Use PROACTIVELY for advanced IaC, state management, or infrastructure automation.
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。
Deploy and configure the Havoc C2 framework with teamserver, HTTPS listeners, redirectors, and Demon agents for authorized red team operations.
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 malware command-and-control (C2) communication protocols to understand beacon patterns, command structures, data encoding, and infrastructure. Covers HTTP, HTTPS, DNS, and custom protocol C2 analysis for detection development and threat intelligence. Activates for requests involving C2 analysis, beacon detection, C2 protocol reverse engineering, or command-and-control infrastructure mapping.
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 reusable Terraform modules with proper structure, variables, outputs, and state management for infrastructure as code. Use when users request "Terraform setup", "infrastructure as code", "IaC module", "cloud provisioning", or "Terraform module".
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。
Estimates infrastructure needs based on traffic forecasts, workload analysis, and performance requirements with sizing recommendations and cost trade-offs. Use for "capacity planning", "infrastructure sizing", "resource estimation", or "scalability planning".
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。
You are helping a penetration tester enumerate infrastructure services on
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。
Data structures and algorithms for AI agent episodic memory. Covers vector stores (HNSW, IVF, PQ), temporal indexing, knowledge graphs with triple stores, hierarchical summarization, forgetting curves, working/long-term/ procedural memory, and memory consolidation. Deep analysis of MemGPT/Letta, Zep/Graphiti, Mem0, and the Stanford generative agents memory architecture. Teaches the CS fundamentals behind how agents remember, retrieve, and forget. Activate on: "agent memory", "episodic memory", "vector search algorithm", "HNSW", "memory retrieval", "forgetting curve", "knowledge graph memory", "MemGPT", "Letta", "Zep", "Mem0", "memory consolidation", "temporal retrieval", "agent long-term memory", "memory layer". NOT for: conversation protocol design (use agent-conversation-protocols), agent infrastructure selection (use agentic-infrastructure-2026), building RAG pipelines (use ai-engineer).
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。
Advanced CV for infrastructure inspection including forest fire detection, wildfire precondition assessment, roof inspection, hail damage analysis, thermal imaging, and 3D Gaussian Splatting reconstruction. Expert in multi-modal detection, insurance risk modeling, and reinsurance data pipelines. Activate on "fire detection", "wildfire risk", "roof inspection", "hail damage", "thermal analysis", "Gaussian Splatting", "3DGS", "insurance inspection", "defensible space", "property assessment", "catastrophe modeling", "NDVI", "fuel load". NOT for general drone flight control, SLAM, path planning, or sensor fusion (use drone-cv-expert), GPU shader development (use metal-shader-expert), or generic object detection without inspection context (use clip-aware-embeddings).
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。
AWS CDK infrastructure builder using TypeScript with L2/L3 constructs and Well-Architected patterns. Activate on: AWS CDK, CDK construct, CDK stack, CDK pipeline, AWS infrastructure as code TypeScript, L2 construct, CDK patterns. NOT for: Terraform IaC (use terraform-module-builder), Kubernetes manifests (use kubernetes-manifest-generator), serverless framework (use devops-automator).
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。
Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Compares the version-pinned A2A, MCP, and JSON-RPC role boundaries covered by this bundle; OpenAI and LangChain-specific APIs require their own current sources. Teaches when to use rigid schemas versus free-form content with validation, typed versus untyped boundaries, and streaming versus batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).
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。
人が行う必要のあるサービス設定や移行作業を、対話型のbashスクリプトにまとめます。画面操作の案内、秘密情報の入力、設定値の保存を段階ごとに進めます。
繰り返すLLMへのAPIリクエストで、共通の指示や資料を再利用しやすく並べるスキル。キャッシュ利用量と費用、応答時間を確認し、構成の見直しを支援します。
Webアプリの本番公開に向けて、Docker構成やテスト・公開の自動化を整え、更新方式の選定から稼働確認、障害時の復旧手順まで支援するスキル。
業務ロジックをデータベースや外部APIから分離し、明確な境界とテストを設けながら、新規サービスの設計や既存コードの段階的な改修を支援するスキル。
ドメインのサブドメイン、SSL証明書、登録情報、DNSレコードを調べるスキル。複数ドメインの一括調査や登録状況の推定に対応し、結果をJSONで返します。
Dark-themed SVG architecture/cloud/infra diagrams as HTML.
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。
Documentation reference for using Browser Use Cloud — the hosted API and SDK for browser automation. Use this skill whenever the user needs help with the Cloud REST API (v2, v3, or v4), browser-use-sdk (Python or TypeScript), X-Browser-Use-API-Key authentication, cloud sessions, browser profiles, profile sync, CDP WebSocket connections, stealth browsers, residential proxies, CAPTCHA handling, webhooks, workspaces, skills marketplace, liveUrl streaming, pricing, or integration patterns (chat UI, subagent, adding browser tools to existing agents). Also trigger for questions about n8n/Make/Zapier integration, Playwright/ Puppeteer/Selenium on cloud infrastructure, or 1Password vault integration. Do NOT use this for the open-source Python library (Agent, Browser, Tools config) — use the open-source skill instead.
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。
Retrieve active cyber-threat intelligence — malware IOCs, C2 infrastructure, and CISA known-exploited vulnerabilities — filterable by type, source, and severity. Use when the user asks about current cyber threats, IOCs, or actively exploited CVEs.
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 validated architecture, workflow, sequence, data-flow, lifecycle/state, entity-relationship, class/interface, tree, timeline, and execution waterfall diagrams as explorable standalone HTML with inline SVG, dark/light themes, optional motion, and image/SVG/WebM export. Accept plain-language requirements or Mermaid; inspect repository evidence for code-backed diagrams. Use when visualizing infrastructure, cloud/security networks, API calls, data pipelines, ETL/ELT, state machines, database schemas, class contracts, module hierarchies, incident/release histories, or request and agent-run timings. Also use for everyday subjects with steps, parts, relationships, or states: leave and travel plans, applications and approvals, renting conversations, money or document flows, and order progress. Not for numeric charts or dashboards.
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 and manage a DDD bounded context with standard directory structure. Use when starting a new subdomain, splitting a monolith into bounded contexts, or scaffolding the domain/application/infrastructure layout for a fresh module.
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 checking whether a site has a correctly configured favicon, auditing `<link rel='icon'>` tags in the `<head>`, or setting up favicon infrastructure for a new project.
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。
Add security scanning to CI/CD with Strix — GitHub Actions, GitLab CI, or any pipeline — so every pull request gets a diff-scoped AI pentest that blocks vulnerable code before it merges, with results as PR comments and SARIF uploaded to code scanning. Covers both the self-hosted open-source CLI (runs in your runner) and the managed app.strix.ai platform (GitHub/GitLab app or API, no runner infra). Use when the user asks to add security scanning, SAST/DAST, pentesting, vulnerability checks, or automated security review to their CI pipeline, pre-merge gate, or PR workflow.
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。
Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.
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 implement VPCs and networking. Configure subnets, route tables, and security groups. Use when setting up AWS network infrastructure.
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。