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概要と使いどころ
Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, schedul...
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This skill covers detecting sophisticated cyber-physical attacks that follow the Stuxnet attack pattern of modifying PLC logic while spoofing sensor readings to hide the manipulation from operators. It addresses PLC logic integrity monitoring, physics-based process anomaly detection, engineering workstation compromise indicators, USB-borne attack vectors, and multi-stage attack chain detection spanning IT-to-OT lateral movement through to process manipulation.
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Detect abuse of legitimate Windows binaries (LOLBins) used for living off the land attacks. Monitors process creation, command-line arguments, and parent-child relationships to identify suspicious LOLBin execution patterns.
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Detect malicious scheduled task creation and modification using Sysmon Event IDs 1 (Process Create for schtasks.exe), 11 (File Create for task XML), and Windows Security Event 4698/4702. The analyst correlates task creation with suspicious parent processes, public directory paths, and encoded command arguments to identify persistence and lateral movement via scheduled tasks. Activates for requests involving scheduled task detection, Sysmon persistence hunting, or T1053.005 Scheduled Task/Job analysis.
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Detects rootkit presence on compromised systems by identifying hidden processes, hooked system calls, modified kernel structures, hidden files, and covert network connections using memory forensics, cross-view detection, and integrity checking techniques. Activates for requests involving rootkit detection, hidden process discovery, kernel integrity checking, or system call hook analysis.
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This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.
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Automates the enrichment of raw indicators of compromise with multi-source threat intelligence context using SOAR platforms, Python pipelines, or TIP playbooks to reduce analyst triage time and standardize enrichment outputs. Use when building automated enrichment workflows integrated with SIEM alerts, email submission pipelines, or bulk IOC processing from threat feeds. Activates for requests involving SOAR enrichment, Cortex XSOAR, Splunk SOAR, TheHive, Python enrichment pipelines, or automated IOC processing.
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。
Establish a structured operational process to triage, test, and deploy Microsoft Patch Tuesday security updates within risk-based remediation SLAs.
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 RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials. Supports Windows, Linux, and macOS memory forensics. Activates for requests involving memory forensics, RAM analysis, volatile data examination, process injection detection, or memory-resident malware investigation.
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。
システムログを分析してエラーの根本原因を特定し、段階的に深堀りしていくデバッグ専門家スキル。 アプリケーションログ、システムログ、クラウドサービスログなど様々な形式に対応。 5 Whys、タイムライン分析、Fishbone分析などのRCA（根本原因分析）手法を用いて 問題の本質を突き止め、再発防止策まで提案する。 Use when analyzing system logs to find error root causes, debugging application issues, or performing technical post-mortem analysis with log data. For organizational incident management processes (post-incident review, corrective action plans, incident reports without log data), use incident-rca-specialist instead. Triggers: "analyze this log", "find the root cause", "debug this error", "why is this failing", "log analysis", "what caused this crash", "troubleshoot this issue"
SoX（Sound eXchange）を使用した音声処理の専門スキル。音声ファイルの変換、編集、エフェクト適用を効率的に支援。フォーマット変換（WAV/MP3/FLAC/OGG/AIFF等）、音声編集（トリム、結合、分割、フェード）、エフェクト（ノイズ除去、ノーマライズ、EQ、リバーブ、コンプレッサー）、分析（soxi、stat、spectrogram）など幅広い操作をカバー。Use when converting audio formats, applying audio effects, trimming/splitting audio files, normalizing volume, removing noise, generating spectrograms, or processing audio for podcasts/music production.
docling CLIを使用したドキュメント変換スキル。PDF、DOCX、PPTX、HTML、画像、Excel等のあらゆるドキュメントをMarkdown、JSON、YAML、HTML、テキストに変換。OCR対応で画像内テキストも抽出可能。Use when converting documents to Markdown or other formats, extracting text from PDFs, processing scanned documents with OCR, or converting office documents. Argument hint: [file_path] [--to md|json|yaml|html|text] [--ocr-lang ja] [--output output_dir]
Generate audit-ready internal control design documents from As-Is business process inventories. Produces control IDs, assertion mappings, procedures, SoD analysis, KPIs, materiality thresholds, and implementation roadmaps. Use when building internal controls for new audit engagements, SOX/J-SOX compliance, or process improvement initiatives.
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インシデント発生後の振り返りと根本原因分析を体系的に実施するスキル。 ログファイル解析や技術デバッグが必要な場合は log-debugger を使用すること。 本スキルはインシデント管理プロセス（タイムライン構築、影響評価、 是正措置計画、再発防止策）に特化する。ログデータの分析ではなく、 組織的な振り返りプロセスと是正措置の策定が主目的である。 Use when conducting post-incident reviews without log analysis, creating corrective action plans, or performing organizational root cause analysis focused on process improvement. NOT for log file debugging. Triggers: "post-incident review", "corrective action plan", "incident report作成", "再発防止策", "RCAレポート", "是正措置", "インシデント振り返り"
Signpost (not a knowledge pack) for the railway RAMS and signalling assurance standards: EN 50126-1:2017 and EN 50126-2:2017 (both with A1:2024) for the RAMS process, EN 50128:2011 (A1:2020, A2:2020) for software for railway control and protection systems, and EN 50129:2018 and EN 50129:2026 for safety-related electronic systems for signalling, plus the free CSM regulations and ORR guidance that cover the risk-process need. Contains no source content: each row carries only the designation, title, edition, owner, redistributability status, and an official URL. Use when you need to identify, cite, or locate one of these documents. No in-repo pack covers these standards.
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Arlo Belshee의 6단계 네이밍 프로세스와 Clean Code 네이밍 규칙을 적용해, 여러 파일에 흩어진 개별 이름 스멜(타입 반복·-er/-Utils·불용어·축약어 등)을 탐지하고 배치 교체하여 코드 가독성 향상. 단, 하나의 긴 메서드를 통째로 관통(grouping→extract→rename)하는 것은 /intent-revealing-names가 적합. /naming-process로 호출.
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。
Track build processing, find latest builds, and clean up old builds with asc. Use when managing build retention or waiting on processing.
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。
Knowledge base from the SD-22 DMSMS Guidebook (DSPO, FY24 working draft). Use for managing Diminished Manufacturing Sources and Material Shortages (DMSMS) and obsolescence across a long-lived system's life cycle: the five-step process (Prepare, Identify, Assess, Analyze, Implement) plus the Strategize overlay; standing up a DMSMS Management Team (DMT) and Management Plan (DMP); risk-based monitoring and surveillance (the risk cube, predictive tools, vendor surveys, GIDEP/DLA PDNs, critical-materials analysis); health assessments and resolution timing; costing and selecting resolutions (life-of-need buys, substitutes, redesign, technology refreshment) by AoA/BCA; and budgeting/executing resolutions through modification funding and the ECP process. Defense-sustainment / DoD-acquisition framing throughout. Does NOT teach general systems engineering, parts-management standards, or contracting law in depth, and does not reproduce DoD policy text or the source's tables and figures.
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Knowledge base from NIST SP 800-160 Vol 1 (Engineering Trustworthy Secure Systems) and Vol 2 (Developing Cyber-Resilient Systems). Use for systems security engineering (SSE): the three SSE framework contexts (problem/solution/trustworthiness), the 30+ design principles for trustworthy secure design, trustworthiness and assurance/assurance cases, security across the ISO/IEC/IEEE 15288 life-cycle process groups, and the Vol 2 cyber-resiliency engineering framework — 4 goals (anticipate/withstand/recover/adapt), objectives, 14 techniques, implementation approaches, and design principles for the APT/adverse-conditions threat model. Bridges systems engineering and the NIST security cluster (CSF/SSDF/RMF). Does not reproduce ISO/IEC/IEEE 15288 process text, nor cover SP 800-53 control catalogs in depth.
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。
Knowledge base from the FAA System Safety Handbook (Dec 30, 2000). Use for system safety as a specialty within systems engineering: the five-step safety risk management process (mandated by FAA Order 8040.4 and the AMS), the severity-by-likelihood risk matrix and acceptance bands, the Safety Order of Precedence, system-description models (5M, SHEL(L)), the hazard-analysis activities (PHL/PHA/RHA/SSHA/SHA/O&SHA/HHA), integrated system hazard analysis, the analysis techniques (FTA, FMEA/FMECA, Fault Hazard, Common Cause, Sneak Circuit, Energy Trace), closed-loop hazard tracking (Safety Action Record), and the specialty domains the handbook covers — acquisition-lifecycle safety and contracting (OSA/CSA/SSPP/ISSPP), software safety (control-capability ranking, SHCM, DO-178B), test & evaluation safety, facilities safety, commercial launch safety (AST licensing, expected casualty, MPL/DAMP), system safety training, and Operational Risk Management (ORM) with human/organizational factors. Scope limits: this is a year-2000 FAA how-to; it predates the modern FAA/ICAO Safety Management System (SMS) and Just Culture regulatory frameworks, and many cited orders, advisory circulars, and launch-licensing rules have since been restructured. It is FAA/NAS-centric, leans on MIL-STD-882C, and does not define the SE life-cycle processes themselves (use nasa-npr-7123 / dau-se-guidebook) or reproduce third-party standard text (MIL-STD-882, DO-178B, ISO/IEC/IEEE).
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Knowledge base from the DoD Systems Engineering Guidebook (OUSD R&E, February 2022). Use for the DoD SE process model — the 16 SE processes (8 technical management + 8 technical) mapped to ISO/IEC/IEEE 15288, the event-driven technical reviews and audits across the Major Capability Acquisition life cycle (ASR, SRR, SFR, PDR, CDR, SVR/FCA, PRR, PCA), the Systems Engineering Plan (SEP), risk/issue/opportunity management, TPMs and leading indicators, system-of-systems and digital engineering, and the 24 design considerations (RAM, system safety, HSI, system security engineering, MOSA, supportability, etc.). Acquisition-program oriented: thin on detailed cost estimating, contracting law, and non-DoD or commercial life cycles.
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Knowledge base from the DoD M&Q BoK (the Manufacturing and Quality Engineering Body of Knowledge), v3.0 of July 2025, published by OUSD(R&E). Use for the manufacturing-and-quality view of the defense acquisition life cycle: what M&Q engineers do across the Adaptive Acquisition Framework phases (Pre-MDD, Materiel Solution Analysis, Technology Maturation and Risk Reduction, Engineering and Manufacturing Development, Production and Deployment, Operations and Support); the twelve M&Q threads (A–L) built on the '5 Ms'; manufacturing feasibility and producibility; Manufacturing Readiness Levels and assessments; Key/Critical Characteristics and process capability (Cp/Cpk, SPC); the standards stack (AS6500, AS9100/ISO 9001, AS9103, AS9145); technical reviews (ASR/PDR/CDR/PRR) and milestone gates; DCMA surveillance; industrial base and supply chain; and sustainment (LCSP, IPS, ILA, ISR). Scope is DoD acquisition M&Q practice on the Major Capability Acquisition path — it is a best-practice compilation, not policy, and is thin on detailed shop-floor process engineering, contract law, and the full text of the cited industry standards (which it names but does not reproduce).
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Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.
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Knowledge base from the GAO Technology Readiness Assessment Guide (GAO-20-48G, 2020). Use for evaluating technology maturity in acquisition programs and projects: Technology Readiness Levels (TRL 1–9) and related scales (MRL, IRL), identifying Critical Technology Elements (CTEs), the five-step process for a high-quality TRA, the four characteristics of a reliable TRA (comprehensive, well-documented, credible, defensible), Technology Maturation Plans (TMPs), and using TRA results in knowledge-based, milestone decisions. Assessment/maturity oriented: it measures readiness and frames risk — it is not a full SE process model, cost-estimating, or schedule guide (see sibling packs for those).
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。