「enforcement」の検索結果

Coordinate autonomous pentest skills with dependency enforcement, deconfliction, and emergency stop 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。

Project-orientation workflow (/orient): installs predicate's enforcement into a target project, maps its structure and goal, and authors the persistent conditioning layer (AGENTS.md goal-hierarchy) so every subsequent walk is anchored and gated. Trigger when: - Onboarding a new project into predicate for the first time. - Refreshing an existing project's AGENTS.md hierarchy against the current state of the repository (re-run = refresh). - Prompt contains: /orient, orient workflow, onboard project, project orientation, AGENTS.md hierarchy, persistent conditioning layer.

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。

Real-time work context tracking for session continuity. Maintains task/step state across sessions, tracks progress, manages logs, integrates with phase enforcement.

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。

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

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 NTLM relay attacks through Windows Security Event correlation by analyzing Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB and LDAP signing enforcement across the domain, and detecting NTLM downgrade attacks from NTLMv2 to NTLMv1 using event log analysis.

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。

Deploying Palo Alto Networks Prisma Access for SASE-based zero trust network access using GlobalProtect agents, ZTNA Connectors, security policy enforcement, and integration with Strata Cloud Manager for unified security 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。

Harden LDAP directory services against common attacks including credential harvesting, LDAP injection, anonymous binding, and channel binding bypass. Covers LDAPS enforcement, channel binding, LDAP si

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。

Simulates man-in-the-middle attacks using Ettercap, mitmproxy, and Bettercap in authorized environments to intercept, analyze, and modify network traffic for testing encryption enforcement, certificate validation, and detection capabilities.

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。

Traces ransomware cryptocurrency payment flows using blockchain analysis tools such as Chainalysis Reactor, WalletExplorer, and blockchain.com APIs. Identifies wallet clusters, tracks fund movement through mixers and exchanges, and supports law enforcement attribution. Activates for requests involving ransomware payment tracing, bitcoin wallet analysis, cryptocurrency forensics, or blockchain intelligence gathering.

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。

Android device offensive security, forensic extraction, and mobile app exploitation. Use this whenever the user needs to: break into or bypass the lock screen of an Android phone, extract data from a seized Android device for evidence, analyze or reverse-engineer an APK to find vulnerabilities, intercept communications on an Android device, exploit Android apps via deeplinks, steal crypto wallets or app data, set up rogue WiFi to target a phone, or plan any mobile device investigation or penetration test. Also trigger when the user mentions Android forensics, mobile pentesting, law enforcement phone extraction, device exploitation, WhatsApp or Telegram extraction from a phone, Android app reversing, CVE research for Android, or needing a chain of custody for mobile evidence. Even if the user describes the scenario casually or in another language, if they need to gain access to or pull data from an Android phone, use this skill.

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 service mesh patterns for AI inference traffic management, mTLS, canary releases, policy enforcement, and cross-cluster resilience.

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。

デザイントークンを使わずに直書きされた色・余白・フォントサイズ・角丸・シャドウを検出する。Figma Variables / Tailwind config / CSS custom properties のルールに違反する実装を指摘する。

Expert-level guidance for Flutter production applications: architecture decisions (Clean/Layered/Hexagonal/Feature-First), advanced state management (BLoC/Riverpod/GetX), performance optimization (eliminating jank, memory profiling, reducing rebuild overhead), code review with design pattern enforcement, scalability assessments, native platform integration (MethodChannel/EventChannel/FFI), complex UI challenges (custom render objects, slivers), testing strategies (unit/widget/integration/golden), CI/CD pipeline architecture, build optimization, and accessibility compliance. Triggers: 'architecture decision', 'design pattern', 'performance issue', 'code review', 'production problem', 'scaling concerns', 'best practices', 'technical debt', 'refactoring strategy'. Essential for complex enterprise apps, critical production debugging, architectural refactors, or when choosing between competing technical approaches.

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。

Act as FriendlyBet's CEO and primary front door for every FriendlyBet request through automatic company preflight. Own end-to-end routing, planning, execution coordination, department orchestration, decision-rights enforcement, quality gates, board-style reporting, and escalation only for strategic, legal, brand, cost, risk, or taste decisions. Use by default in FriendlyBet threads, with full department planning for broad, ambiguous, strategic, cross-functional, or outcome-driven requests such as SEO, new features, multi-sport expansion, product direction, release execution, company operations, or agent coordination.

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。

Layer-by-layer remediation loop using adversarial audits, targeted fixes, and fresh-run verification enforcement

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。

Execute recursive breadth-before-depth ideation discovery with Deep Think, CX gate enforcement, and feature deepening

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 and optimize repositories for AI coding agents. Creates minimal AGENTS.md, CLAUDE.md symlink, docs/REQUIREMENTS.md, docs/BUSINESS-RULES.md, feedback loops, and deterministic enforcement (Claude Code hooks, OpenCode plugins). Use when user wants to make a repo AI-friendly, set up AGENTS.md/CLAUDE.md, document requirements/business rules for AI, add pre-commit hooks for AI workflows, or optimize codebase structure for coding 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。

Use when working with Danger Js — danger JS automated code review management. Covers Dangerfile configuration, PR rule enforcement, plugin management, CI integration, and custom rule development. Use when managing Danger JS rules, configuring PR checks, debugging Dangerfile execution, or enforcing team code review policies.

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 working with Calico — calico networking and security management for Kubernetes. Covers network policy enforcement, BGP configuration, IPAM management, Felix agent status, Typha health, WireGuard encryption, and global network sets. Use when managing Calico network policies, debugging routing issues, configuring BGP peering, or monitoring Felix/Typha health.

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 working with Cloud Custodian — cloud Custodian policy engine management. Covers policy authoring, dry-run execution, resource filtering, action enforcement, multi-cloud support (AWS/Azure/GCP), Lambda deployment, compliance reporting, and policy organization. Use when managing Cloud Custodian policies, auditing cloud resources, enforcing compliance rules, or reviewing policy execution 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。

Use when working with Cilium — cilium eBPF-based networking and security management for Kubernetes. Covers network policy enforcement, eBPF map inspection, Hubble flow visibility, cluster mesh, endpoint health, service load balancing, and identity management. Use when managing Cilium network policies, debugging connectivity, monitoring traffic flows with Hubble, or configuring cluster mesh.

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。

AI agent system prompts cannot serve as the sole enforcement layer — guardrails must be implemented at the API gateway and token-permission level, not

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 a task requires exhaustive unabridged output, complete files, or strict prevention of placeholders and skipped code.

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 Claude Code skills following Anthropic best practices. Use when creating new skills, modifying skill-rules.json, understanding trigger patterns, working with hooks, debugging skill activation, or implementing progressive disclosure. Covers skill structure, YAML frontmatter, trigger types (keywords, intent patterns, file paths, content patterns), enforcement levels (block, suggest, warn), hook mechanisms (UserPromptSubmit, PreToolUse), session tracking, and the 500-line rule.

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。