3,434 件 ・ 関連度順
概要と使いどころ
Three.js interaction - raycasting, controls, mouse/touch input, object selection. Use when handling user input, implementing click detection, adding camera controls, or creating interactive 3D experiences.
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。
Set up Convex authentication with proper user management, identity mapping, and access control patterns. Use when implementing auth flows, setting up OAuth providers, or adding role-based access control.
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。
The science of learning through controlled experimentation. A/B testing isn't about picking winners—it's about building a culture of validated learning and reducing the cost of being wrong. This skill covers experiment design, statistical rigor, feature flagging, analysis, and building experimentation into product development. The best experimenters know that every test, positive or negative, teaches something valuable. Use when "a/b test, experiment, hypothesis, statistical significance, sample size, feature flag, variant, control, treatment, p-value, conversion rate, test winner, split test, experimentation, testing, statistics, feature-flags, hypothesis, growth, optimization, learning, validation" mentioned.
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。
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
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。
Specialized skill for testing time-dependent logic using TimeProvider. Use when testing DateTime, controlling time flow, handling timezone conversions, and testing expiration logic. Covers TimeProvider abstraction, FakeTimeProvider time control, time freezing and fast-forwarding. Keywords: datetime, time testing, TimeProvider, FakeTimeProvider, DateTime.Now, time-dependent, cache expiration, token expiration, Microsoft.Bcl.TimeProvider, GetUtcNow, SetUtcNow, Advance, time freeze, time freezing, time fast-forward
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。
Tests APIs for Broken Function Level Authorization (BFLA) vulnerabilities where regular users can invoke administrative functions or access privileged API endpoints by directly calling them. The tester identifies admin and privileged endpoints, then attempts to access them with regular user credentials by manipulating HTTP methods, URL paths, and request parameters. Maps to OWASP API5:2023 Broken Function Level Authorization. Activates for requests involving BFLA testing, admin endpoint bypass, function-level access control testing, or API privilege escalation.
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。
This skill covers detecting anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems. It addresses function code monitoring, register range validation, timing analysis, unauthorized client detection, and deep packet inspection for malformed Modbus frames. The skill leverages Zeek with Modbus protocol analyzers, Suricata IDS with OT rules, and custom Python-based detection using Markov chain models for normal Modbus transaction sequences.
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。
Detects command-and-control (C2) communications tunneled through DNS protocol including DNS tunneling tools (Iodine, dnscat2, dns2tcp, Cobalt Strike DNS beacon), domain generation algorithms (DGA), encoded payload delivery via TXT/CNAME records, and DNS beaconing patterns. Covers Shannon entropy analysis of query subdomains, statistical anomaly detection, ML-based DGA classification, passive DNS correlation, and Zeek/Suricata signature development. Activates for requests involving DNS-based C2 detection, DNS tunnel identification, suspicious DNS traffic investigation, or DGA domain classification.
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。
Build a vulnerability exception and risk acceptance tracking system with approval workflows, compensating controls documentation, and expiration management.
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。
This skill details how to conduct cloud security audits using Center for Internet Security benchmarks for AWS, Azure, and GCP. It covers interpreting CIS Foundations Benchmark controls, running automated assessments with tools like Prowler and ScoutSuite, remediating failed controls, and maintaining continuous compliance monitoring against CIS v5 for AWS, v4 for Azure, and v4 for GCP.
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。
Build and configure a resilient command-and-control infrastructure using BishopFox's Sliver C2 framework with redirectors, HTTPS listeners, and multi-operator support for authorized red team engagements.
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。
Systematically audit AWS S3 bucket permissions to identify publicly accessible buckets, overly permissive ACLs, misconfigured bucket policies, and missing encryption settings using AWS CLI, S3audit, and Prowler to enforce least-privilege data access controls.
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 intrusion activity against the Lockheed Martin Cyber Kill Chain framework to identify which phases an adversary has completed, where defenses succeeded or failed, and what controls would have interrupted the attack at earlier phases. Use when conducting post-incident analysis, building prevention-focused security controls, or mapping detection gaps to kill chain phases. Activates for requests involving kill chain analysis, intrusion kill chain, attack phase mapping, or Lockheed Martin kill chain framework.
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。
Implements role-based access control with permission matrix, route guards, policy functions, and UI permission hints. Provides middleware/guards, helper utilities, test suggestions, and permission checking patterns. Use when building "RBAC", "permissions", "access control", or "authorization".
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。
Discover a single-page-app's hidden backend API from its public JS bundle, then test that API for broken access control / missing authentication. One of the highest-yield web plays in modern recon — SPAs ship their entire backend route map to the browser, and the API behind them is frequently missing the auth middleware the login page implies. Built from an authorized engagement where this play found an unauthenticated financial API that an ASM scan reporting hundreds of 'Criticals' completely missed. Use whenever a target serves a JS-heavy SPA (React/Vue/Angular/Next), an 'app'/'console'/'dashboard'/'portal' subdomain, or any `*api*` host shows up in recon. Leaked build artifacts (source maps / .env / .git / asset-manifest) are owned by hunt-source-leak; API version-inventory and behavioral diffing by hunt-shadow-api; this skill owns mapping a live SPA's backend routes from its JS bundle and testing them for broken access control / missing auth.
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。
Hunt CORS Misconfiguration — origin-reflection with credentials, null-origin trust, subdomain-regex bypass (unanchored vs unescaped-dot vs prefix-only), pre-flight (OPTIONS) gating bypass, postMessage origin checks. High only when an attacker-controlled origin can perform a CREDENTIALED cross-origin read of sensitive data and you have proven it in a browser. Use when testing API endpoints, SPAs, or any app emitting Access-Control-* headers.
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。
Control Home Assistant smart home devices, run automations, and receive webhook events. Use when controlling lights, switches, climate, scenes, scripts, or any HA entity. Supports bidirectional communication via REST API (outbound) and webhooks (inbound triggers from HA automations).
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。
Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives. Critical focus on sandboxing, security, and handling the unique challenges of vision-based control. Use when: computer use, desktop automation agent, screen control AI, vision-based agent, GUI 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。
運用者が設定したTeamサーバーの更新を、指定担当のNight Watchに引き継ぎ、既存の更新機構による検証・復旧・完了確認まで進めるスキル。
OpenClawのブラウザ操作で、ログイン状態やタブを確認しながら複数手順の作業を進めます。古くなった操作対象の参照やタイムアウトへの対処も扱います。
DiscordにつながるOpenClawのエージェントやセッションへ質問を送り、送信先を確認したうえで、セッション側の判断に任せる投稿や明示指定の投稿を扱います。
OpenClaw全体の品質検証を継続し、不具合の再現から根本原因の修正、レビュー、反映確認まで進めます。実環境や負荷の検証結果を、再開可能な報告書に記録します。
Spotifyの曲検索や再生・一時停止、曲送りをターミナルから操作し、再生先デバイスの一覧確認や切り替え、現在の再生状況の確認まで行います。
macOSの画面を確認し、対象のアプリやウィンドウを指定してクリック・文字入力・キー操作などを行い、操作後の結果まで確かめるスキル。