「cat」の検索結果

既知の不審なドメインやIPを起点に、DNS履歴や登録情報から関連する攻撃基盤を探索。関係図を作り、既知の命名パターンに合う新たなドメインを監視します。

• 既知の不審IPから関連ドメイン探索
• 攻撃者のC2基盤の関係図作成
• 既知の命名パターンに合うドメイン監視

Windowsに残るアプリやドライバーの記録を解析し、不審なファイルや削除済みの実行ファイルの痕跡を調べ、ハッシュ照合と時系列整理でインシデント調査を支援します。

• 削除済み実行ファイルの痕跡調査
• 事件発生期間中の導入ソフト確認
• ファイルハッシュのマルウェア照合

ZeekやNetFlowの通信記録から、ランサムウェアに関連する定期通信、TOR接続、大量の外向き転送などを調べ、リスクスコアと時系列レポートにまとめます。

• 稼働中のランサムウェア通信の探索
• 暗号化前のデータ持ち出し調査
• 定期通信やTOR接続の確認

Microsoft Entra IDの認証設定や管理者権限、条件付きアクセス、休眠・ゲストアカウントを監査し、設定の抜けや過剰権限を整理するスキル。

• Azureの認証設定と管理者権限の監査
• 買収先テナントの統合前評価
• 休眠アカウントと特権ゲストの確認

通信の記録からDNS・ICMP・HTTPに隠されたマルウェアの通信経路を調べ、ドメイン名の特徴や通信量の異常を手掛かりに、不審な通信の候補を整理するスキル。

• 不審なDNS・ICMP・HTTP通信の調査
• 通信記録から隠れた指令経路を探したいとき
• 異常な通信による情報流出の可能性調査

Go製マルウェアの実行ファイルをGhidraで解析し、関数名や依存ライブラリ、埋め込み文字列を調べます。難読化や名前の削除で読みにくい検体の構造把握を支援します。

• Go製マルウェア検体の構造調査
• 削除・難読化された関数名の復元
• 埋め込まれたモジュールや依存関係の確認

WeKnoraの知識ベースや文書をCLIから管理し、検索や資料に基づく質問応答を行うための共通ガイドです。認証、JSON出力の読み方、エラー時の対応を扱います。

• WeKnoraの認証を設定したいとき
• 知識ベースや登録文書の管理
• 蓄積した資料の検索と質問応答

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

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。

Verify a research claim or academic citation by tracing it through publication → methodology → raw data → independent replication. Routes through perplexity-research for the actual web lookup, then formats results as a citation-checked brain page. Use when a book/article/conversation cites a study and you want to confirm the claim is real, replicated, and accurately characterized.

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。

Information Security Management System (ISMS) audit expert for ISO 27001 compliance verification, security control assessment, and certification support. Use when the user mentions ISO 27001, ISMS audit, Annex A controls, Statement of Applicability (SOA), gap analysis, nonconformity management, internal audit, surveillance audit, or security certification preparation. Helps review control implementation evidence, document audit findings, classify nonconformities, generate risk-based audit plans, map controls to Annex A requirements, prepare Stage 1 and Stage 2 audit documentation, and support corrective action workflows.

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 meeting transcripts and recordings to surface behavioral patterns, communication anti-patterns, and actionable coaching feedback. Use this skill whenever the user uploads or points to meeting transcripts (.txt, .md, .vtt, .srt, .docx), asks about their communication habits, wants feedback on how they run meetings, requests speaking ratio analysis, mentions filler words or conflict avoidance, or wants to compare their communication across time periods. Also trigger when users mention tools like Granola, Otter, Fireflies, or Zoom transcripts. Even if the user just says "look at my meetings" or "how do I come across in meetings" — 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。

Senior SecOps engineer skill for application security, vulnerability management, compliance verification, and secure development practices. Runs SAST/DAST scans, generates CVE remediation plans, checks dependency vulnerabilities, creates security policies, enforces secure coding patterns, and automates compliance checks against SOC2, PCI-DSS, HIPAA, and GDPR. Use when conducting a security review or audit, responding to a CVE or security incident, hardening infrastructure, implementing authentication or secrets management, running penetration test prep, checking OWASP Top 10 exposure, or enforcing security controls in CI/CD pipelines.

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。

Cascades strategy from boardroom to individual contributor. Detects and fixes misalignment between company goals and team execution. Covers strategy articulation, cascade mapping, orphan goal detection, silo identification, communication gap analysis, and realignment protocols. Use when teams are pulling in different directions, OKRs don't connect, departments optimize locally at company expense, or when user mentions alignment, strategy cascade, silo, conflicting OKRs, or strategy communication.

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 maintain one coherent company story across all audiences — employees, investors, customers, candidates, and partners. Detects narrative contradictions and ensures the same truth is framed for each audience's needs. Use when preparing investor updates, all-hands presentations, board communications, recruiting narratives, crisis communications, or when user mentions company narrative, messaging consistency, storytelling, all-hands, investor update, or crisis communication.

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。

Discovers requirements and designs an end-to-end governed agentic analytics solution using Knowledge Catalog and Managed Service for Apache Spark (Lightning Engine). Use when designing data science and analytics workflows across structured and unstructured distributed data (including in S3, Azure Blob, AlloyDB, and Iceberg), establishing metadata governance with Knowledge Catalog aspect types, or grounding agentic IDEs (VS Code, Antigravity) by using the Google Cloud Data Agent Kit. Don't use for provisioning borderless data lakehouse infrastructure (use google-cloud-solution-agentic-ai-borderless-data-lakehouse 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。

Processes GCP infrastructure design and deployment workflows within Application Design Center (ADC). Use when: - Designing GCP infrastructure with Terraform. - Validating local HCL. - Performing best-practice plan scans. - Importing templates to Application Design Center (ADC). - Deploying templates. - Troubleshooting deployment failures. Boundaries: - Only use for GCP-specific cloud infrastructure. - Only use for Terraform coding within the ADC context.

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。

Find, evaluate, and download common purchasable CAD parts from step.parts, including named off-the-shelf actuators, servos, motors, electronics boards, connectors, screws, bolts, nuts, washers, bearings, standoffs, and other catalog components. Use when Codex needs to search the hosted step.parts catalog before creating simplified placeholder geometry, resolve fuzzy part names, standards, aliases, or dimensions, choose a matching part, fetch a canonical .step file, verify checksums, or use the step.parts API/OpenAPI/catalog endpoints for standard part discovery.

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 Chrome/Brave + macOS Computer Use from inside the browser — zero CDP fingerprint, real sessions; mandatory for visual deploy verification. Drive clickwork yourself. USE WHEN verify deploy, confirm UI, screenshot verification, computer use, macos automation, debug web, troubleshoot, visual check, motion/animation bug, jank, transition stutter, scrub a flow, console logs/errors, runtime/JS/react errors, mismatch warning, network traffic/log, HAR/pcapng export, hydration/blank-page debug, flash then blank/page broken, why is this not working/what's happening on the page, authenticated page, bot detection bypass, reproduce bug, drive native app, about to ask the operator to click/navigate/fill a form/log in/approve OAuth, OAuth consent flow, complete a web login, do this in your browser. NOT FOR residential-proxy crawling (BrightData) or social actor scraping (Apify).

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。

Zero-context verification that every bibliographic entry in the paper is real, correctly attributed, and used in a context the cited paper actually supports — catching hallucinated authors, wrong years, fabricated venues, version mismatches, and wrong-context citations. Use when user says "审查引用", "check citations", "citation audit", "verify references", "引用核对", or before submission to ensure bibliography integrity.

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。

Communications-domain literature review with Claude-style knowledge-base-first retrieval. Use when the task is about communications, wireless, networking, satellite/NTN, Wi-Fi, cellular, transport protocols, congestion control, routing, scheduling, MAC/PHY, rate adaptation, channel estimation, beamforming, or communication-system research and the user wants papers, related work, a survey, or a landscape summary.

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 WizTelemetry Notification extension for KubeSphere, including installation, configuration, troubleshooting, notification channel setup, alert routing, and silence 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。

Research every provider behind Pipecat's services for new models and API affordances, writing per-service reports and local branches for clear-cut updates; publishing is scripts/provider-watch/publish.py's job, run outside 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。

Writes the missing CARLA documentation that the audit found — Python API entries in PythonAPI/docs/*.yml, sensors in ref_sensors.md, catalogue actors, broken links and nav entries — one audit category at a time, in CARLA's house style. Use when the user asks to "document this feature", "write the docs for X", "fix the audit findings", or names a category such as "the Python API part".

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。

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

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。