「guard」の検索結果

コマンド実行やファイル編集、入力・終了時のイベントを条件で検知し、危険な操作や機密ファイルの変更に警告・ブロックを設定するルールを作るスキル。

• 危険なコマンドをブロックしたいとき
• 機密ファイルの編集に警告したいとき
• 編集時のデバッグコード検知

Djangoでメール送信やPDF生成などをバックグラウンド処理に移し、Celeryによる定期実行、失敗時の再試行、処理の連結、監視とテストを設計するスキル。

• メール送信やPDF生成を裏で実行したいとき
• 在庫更新や通知を定期実行したいとき
• 再試行と重複処理の防止を設計したいとき

DartとFlutterのコード作成・レビューで、状態管理、画面遷移、通信、例外処理、テストの実装パターンを参照し、アプリの構成を整えるスキル。

• 新機能の状態管理を選びたいとき
• null処理や非同期処理のレビュー
• ログイン状態で画面遷移したいとき

Full safety mode: destructive command warnings + directory-scoped edits. (gstack)

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。

Safety guardrails for destructive commands. (gstack)

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。

Ensure async-path backend code that could block the asyncio event loop is protected by a teeth-verified runtime anchor in tests/blocking_io/. Use when changing backend Python under app/, packages/harness/deerflow/, or scripts/, when running a blocking-IO triage round over the whole repo, or when a reviewer/CI asks for blocking-IO coverage. Runs a deterministic scan (changed-lines or full-repo), routes each candidate, drafts/extends an anchor, and proves it fails when the blocking IO regresses.

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。

Monitor provider health, circuit-breaker states, p50/p95/p99 latency metrics, and budget guard alerts. Inspect connection cooldowns and model lockouts in real time.

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。

Render-correctness doctrine for scene-to-scene seams in HyperFrames launch videos — the prerequisites that make transitions composite correctly on the master timeline. Load when assembling the master timeline / index.html, when a white flash appears at a cut or crossfade seam (especially on dark films), when reasoning about why a transition opacity dip shows through, or when verifying the render-side mechanics of how overlapping scene wrappers blend. Covers the opaque stage-ground (#root background) white-flash guard and how the injector overlaps wrappers, holds final frames, ping-pongs tracks, and stamps lint-clean template code onto the master timeline. Does NOT contain the per-transition catalog — see the transition registry for individual transition entries.

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。

Command-line interface for Pioneer Rekordbox 6/7 - DJ library and live-deck control via guarded SQLCipher master.db access (pyrekordbox) + virtual MIDI mapping. Provides library inspection, playlist creation/add/clear, and live-deck mixing (play/sync/crossfade/EQ). Pioneer ships no playback REST API; this harness combines the only two real surfaces (encrypted DB + MIDI) into one agent-native CLI.

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。

Configure agy-auto PreToolUse security gate to run Antigravity CLI (agy) unattended with layered policy controls instead of --dangerously-skip-permissions.

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。

Secure AI coding agents (Claude Code, Cursor, Codex, Copilot) with permission boundaries, secret protection, code review gates, and safe sandbox configurations for team environments.

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 spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.

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。

Autonomous DevSecOps & FinOps Guardrails. Orchestrates Gemini 3 Flash to audit Linux Kernel patches, Terraform cost drifts, and K8s compliance.

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 on complex multi-step tasks, when a session is getting long (40+ tool calls), when the agent starts ignoring rules it followed earlier, when conventions drift, when output quality seems to degrade, or after any context compaction event. Prevents long-session corruption AND context compaction amnesia through behavioral self-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。

Design and implement Arduino integration with Azure IoT Hub and IoT Edge, including secure provisioning, resilient telemetry, command handling, and production guardrails.

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。

How SGLang's runtime configuration and process-global state are organized (RuntimeContext tiers, publish + namespace config bags, the pristine ServerArgs seed, override entry points, resource/stream/buffer leases, per-forward flags), the CI guardrails that enforce the design, and the idioms for developing and testing against it. Load this before touching server_args, model overrides, module-level state, or per-forward state in sglang.

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 sophisticated cyber-physical attacks that follow the Stuxnet pattern of modifying PLC logic while spoofing sensor readings to hide the manipulation, using PLC logic integrity monitoring (Claroty xDome, Nozomi Guardian) and physics-based process anomaly detection. Use when hunting for IT-to-OT lateral movement or discrepancies between PLC program state and physical process behavior in ICS/SCADA environments.

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。

Install and run Stratus Red Team to detonate granular, MITRE ATT&CK-mapped AWS, Azure, GCP, and Kubernetes attack techniques through their warmup-detonate-revert-cleanup lifecycle, then verify the telemetry they generate. Use to validate that cloud detections (CloudTrail, GuardDuty, Microsoft Sentinel, GCP SCC, Falco) actually fire, or to run a repeatable purple-team exercise generating realistic attacker telemetry.

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。

Scan source code repositories, CI/CD pipelines, and configuration files for exposed AWS credentials using TruffleHog, git-secrets, and AWS-native detection. Use when integrating secrets scanning into CI/CD, auditing repositories (including git history) for historically committed AWS keys, responding to a GuardDuty alert about credential use from an unexpected location, or verifying credential rotation removed all exposed keys.

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。

Deploys anomaly detection for OT/ICS environments using machine learning on OT network baselines, physics-based process models, and Modbus/DNP3/OPC UA traffic analysis to flag deviations, rogue devices, and mismatches against historian data. Use for continuous OT monitoring, baselining deterministic SCADA polling, or investigating alerts from Nozomi Guardian/Dragos needing deeper protocol 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。

Deploy cloud-native deception across AWS, Azure, and GCP using decoy (honey) resources whose only purpose is to generate a high-fidelity alert the instant an attacker touches them: canary IAM access keys, permission-less decoy users/roles/service principals, honey object-storage buckets, and decoy secrets in Secrets Manager / Key Vault / Secret Manager. Wires detection through CloudTrail + EventBridge, Azure Sentinel honeytoken watchlists + Defender, and GCP Cloud Audit Logs, so any use of a decoy is routed to the SOC with near-zero false positives. Use when protecting cloud accounts and data stores, when an org has only on-prem honeypots and needs cloud coverage, when seeding fake AWS keys to catch credential theft and code-leak exposure, or when detecting cloud reconnaissance and lateral movement. Keywords: cloud deception, canary token AWS, honey S3 bucket, decoy IAM credentials, CloudTrail alert, GuardDuty, Sentinel honeytoken, decoy secret, honey service account, cloud honeypot, breach detection.

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。

Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.

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 Microsoft Sentinel as a cloud-native SIEM/SOAR by configuring multi-cloud data connectors (AWS, Azure, GCP), writing KQL detection and hunting queries, and building automated Logic Apps response playbooks. Use when establishing a centralized SOC for multi-cloud environments, migrating from a legacy SIEM, or performing petabyte-scale threat hunting; not for AWS-only setups where Security Hub/GuardDuty suffice or for endpoint EDR needs.

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 harden a Sliver C2 team server (BishopFox's Go-based adversary emulation framework) with multi-protocol listeners (mTLS, HTTP/S, DNS, WireGuard), redirectors, domain fronting, and multi-operator support for authorized red-team operations. Use when standing up resilient C2 for a red-team engagement or generating beacon/session implants that must survive blue-team detection.

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。