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Assess Linux and Windows privilege escalation vectors from existing authorized footholds.

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。

Compare model candidates using weighted metrics and deterministic ranking outputs. Use for benchmark leaderboards and model promotion decisions.

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。

GStack learn method for capturing reusable lessons, triggers, and future retrieval cues after debugging, implementation, or release work.

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Design and implement unit, conformance, integration, timing, boot, trace, video, audio, and regression tests for EMULATORS processors, chips, peripherals, and complete machines. Use when creating a verification strategy for a new emulator, converting hardware documentation into tests, adding diagnostic programs or golden artifacts, measuring behavioral coverage, or proving that components interact correctly.

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 case-law chronicle of this repo's major failures — symptom, root cause, evidence, status, and the rule each battle minted — so nobody re-fights a settled battle or re-proposes a rejected fix. Use when a bug/incident looks familiar ("didn't this happen before?"), when you're about to propose an approach that may have been tried and rejected (e.g. shipping a migration from a package), when someone asks "why does rule X exist" / "why is done-by-lgtm a thing" / "what was incident 988", or when a bug-archaeology run hits the shallow-clone wall and needs the pre-June-2026 history. Trigger phrases: "has this broken before", "why can't packages ship migrations", "why did graduation fail", "why is the green-build lesson a rule", "what did we learn from incident NN". (For a live "build is green but the app is broken" symptom, start at crouton-diagnostics-index. NB keep this description free of any space-then-hash sequence — an unquoted YAML scalar treats space-hash as a comment start and silently truncates.)

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Solves complex, open-ended problems using an evolutionary search mechanism inspired by genetic algorithms. Generates a diverse population of candidate answers, scores them against a rubric, then iteratively applies selection, crossover, and mutation to breed progressively better solutions. Use this skill whenever the user wants to explore a solution space deeply, asks for the "best" answer to a subjective or multi-dimensional problem, wants to evaluate competing approaches and distill the strongest, or uses any of these triggers: "evolutionary search", "genetic algorithm", "evolve an answer", "breed solutions", "population-based search", or phrases like "give me multiple approaches and refine the best one". Also trigger when the problem is complex, open-ended, or has no obvious single correct answer and the user wants a high-quality, well-explored result, not just a quick response.

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联想激活（启动效应等效）。不被用户直接触发，作为「能力层工具函数」由其他Skill调用。给定一个概念，在知识图谱中激活语义相邻的概念网络，返回Top-5邻居摘要给调用方。被 cognitive-ask Step 2c 和 cognitive-capture-fragment Step 2.5 调用。

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Distributed machine learning, data mining, and iterative HPC with Exasol. Covers end-to-end ML pipelines (DISTRIBUTE BY + SET scripts + BucketFS), per-entity federated training with partial_fit and ctx.reset(), batch inference, map-reduce ensemble training, distributed ensemble and SON algorithm for frequent itemset mining (Apriori, FP-Growth, association rules, market-basket analysis), Lua execute script orchestration for iterative algorithms (k-means, SGD, gradient descent), scikit-learn model training, parallel hyperparameter search, per-entity forecasting, anomaly detection, model lifecycle in BucketFS (pickle/joblib/ONNX versioning), GPU acceleration via CUDA SLCs (PyTorch/TensorFlow/RAPIDS), and ML-specific performance tuning (skew, OOM, multi-pass chunking).

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You are an agent architect who has learned the hard lessons of autonomous AI. You've seen the gap between impressive demos and production disasters. You know that a 95% success rate per step means only 60% by step 10.

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。

Installs, configures, and tunes Snort 3 intrusion detection system to monitor network traffic for malicious activity using custom and community rulesets, preprocessors, and alert output plugins on authorized network segments.

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 UEFI bootkit persistence mechanisms including firmware implants in SPI flash, EFI System Partition (ESP) modifications, Secure Boot bypass techniques, and UEFI variable manipulation. Covers detection of known bootkit families (BlackLotus, LoJax, MosaicRegressor, MoonBounce, CosmicStrand), ESP partition forensic inspection, chipsec-based firmware integrity verification, and Secure Boot configuration auditing. Activates for requests involving UEFI malware analysis, firmware persistence investigation, boot chain integrity verification, or Secure Boot bypass detection.

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Map advanced persistent threat (APT) group tactics, techniques, and procedures (TTPs) to the MITRE ATT&CK framework using the ATT&CK Navigator and attackcti Python library. The analyst queries STIX/TAXII data for group-technique associations, generates Navigator layer files for visualization, and compares defensive coverage against adversary profiles. Activates for requests involving APT TTP mapping, ATT&CK Navigator layers, threat actor profiling, or MITRE technique coverage analysis.

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Bootstrap a new or existing project with a small, file-based documentation system so Claude Code keeps context, lessons, and decisions across session restarts instead of starting cold every time. Sets up a handful of markdown files under .claude/ (standing rules, a free-form note to your next session, a phased roadmap, a prioritized backlog, and searchable history/changelog archives) sized and split so the files read every session stay small while the archives grow without ever costing context. Use this whenever someone is starting a new project and asks how to structure it for long-running AI-assisted work, wants Claude to "remember" things between sessions without relying on chat history, asks for a CLAUDE.md + backlog + changelog setup, mentions "session continuity", "persistent context", "project memory system", or is retrofitting an existing codebase that has no such system yet. Also use to explain or extend an already-bootstrapped bottle system (add a rule, start the archival script, add a new backlog section).

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 structuring a multi-session learning roadmap with milestones, gates, and pacing calibrated to learner level and goal.

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。

Compile up to five durable insights from the current conversation for possible addition to CLAUDE.md. Use before clearing context, when asked to remember lessons, or when the user wants project conventions and preferences preserved.

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。

Econometrics skill for instrumental variables and treatment effect estimation. Activates when the user asks about: "instrumental variables", "IV estimation", "2SLS", "two-stage least squares", "endogeneity", "weak instruments", "first stage", "Sargan test", "overidentification", "propensity score matching", "PSM", "average treatment effect", "ATT", "LATE", "local average treatment effect", "endogenous regressor", "instrument validity", "工具变量", "两阶段最小二乘", "内生性", "弱工具变量", "倾向得分匹配", "平均处理效应", "处理效应", "局部平均处理效应"

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Knowledge base from the NASA Fault Management Handbook (NASA-HDBK-1002, Draft 2, April 2012). Use for the systems-engineering discipline of designing what a system does when it fails — the fault/failure/anomaly vocabulary, the five FM strategies (two prevention strategies — design-time fault avoidance and operational failure avoidance — plus three tolerance strategies — failure masking, failure recovery, and goal change), the six FM process activities across NASA mission phases Pre-A to E, response-latency-versus-time-to-criticality (TTC) design trades, fault/failure containment regions and FEPPs, the four redundancy approaches, top-down FM requirements development, FM verification vs. validation, the seven dedicated FM milestone reviews (FMCR/FMARR/FMPDR/FMCDR/FMTRR/FMLRR/FMCERR), FM organizational structure, and mined NASA Lessons Learned. Space-mission oriented (flight/ground/operations); spacecraft examples throughout. IMPORTANT: built from an UNAPPROVED DRAFT — several sections (detailed architecture building blocks, the Assessment & Analysis guidance, and Operations & Maintenance) are placeholders in the source and are thin here. Thin on detailed FDIR algorithms, terrestrial/IT fault management, and any approved-standard terminology that may have changed since Draft 2.

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Procedimiento estructurado de 6 pasos para mejorar, renovar o reconstruir pipelines existentes, carpetas de proyectos individuales, estructuras de documentación o stacks de software. Direccionable como "pipeline optimizer" (para pipelines temáticos completos, p. ej. de software, investigación o desarrollo de videojuegos) o "project-folder optimizer" (para carpetas de proyectos individuales dentro de un pipeline, p. ej. una herramienta de software o proyecto de artículo académico). Se activa ante tareas como "mejorar pipeline X", "optimizar el stack", "reconstruir Y", "renovación", "refactorización de pipeline", "limpiar carpeta de proyecto", "mejorar estructura de carpetas", "unificar convenciones", "consolidación de documentación", "integrar en sistema existente" o cualquier intervención sustancial en estructuras establecidas. Proporciona análisis del estado actual, aclaración del propósito, boceto del estado ideal, plan de brechas, identificación empírica de puntos de dolor y reevaluación con subagentes limpios. Previene estándares paralelos, duplicación y rupturas en el pipeline.

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。

既存のパイプライン、個別プロジェクトフォルダ、ドキュメント構造、またはソフトウェアスタックを改善、改修、再構築するための構造化された6ステップのプロシージャ。「pipeline optimizer」（ソフトウェア、研究、ゲーム開発パイプラインなど、トピック全体のパイプライン対象）または「project-folder optimizer」（単一のソフトウェアツールや論文プロジェクトなど、パイプライン内の個別プロジェクトフォルダ対象）として呼び出し可能。「パイプラインXを改善する」、「スタックを最適化する」、「Yを再構築する」、「改修」、「パイプラインのリファクタリング」、「プロジェクトフォルダのクリーンアップ」、「フォルダ構造の改善」、「規約の統一」、「ドキュメントの統合」、「既存システムへの統合」、または確立された構造に対する実質的な介入タスクで起動。既存資産の調査、目的の明確化、理想像のスケッチ、ギャップ計画、経験的課題の特定、および新しいサブエージェントによる再テストを提供。並行標準の発生、重複、パイプラインの破綻を防止。

Структурированная 6-шаговая процедура для улучшения, реновации или перестройки существующих пайплайнов, отдельных папок проектов, структур документации или стек-технологий. Вызывается как "pipeline optimizer" (для целых тематических пайплайнов, например, пайплайнов разработки ПО, исследований или создания игр) или "project-folder optimizer" (для отдельных папок проектов внутри пайплайна, например, единичного инструмента ПО или проекта статьи). Активируется при выполнении таких задач, как "улучшить пайплайн X", "оптимизировать стек", "перестроить Y", "реновация", "рефакторинг пайплайна", "навести порядок в папке проекта", "улучшить структуру папки", "унифицировать конвенции", "консолидация документации", "интегрировать в существующую систему" или при любом существенном вмешательстве в устоявшиеся структуры. Обеспечивает анализ существующего фонда, уточнение целей, эскиз идеального состояния, план устранения разрывов, эмпирическое выявление проблемных мест и повторное тестирование с помощью свежих субагентов. Предотвращает появление параллельных стандартов, дублирование и сбои в пайплайне.

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。

结构化的6步骤流程，用于改进、改造或重构现有的流水线（pipeline）、独立项目文件夹、文档结构或软件技术栈。可调用为“pipeline optimizer”（针对整个主题流水线，例如软件、研究或游戏开发流水线）或“project-folder optimizer”（针对流水线内的独立项目文件夹，例如单个软件工具或论文项目）。触发于诸如“改进流水线X”、“优化技术栈”、“重构Y”、“改造”、“流水线重构”、“清理项目文件夹”、“改进文件夹结构”、“统一规范”、“文档整合”、“集成到现有系统”或针对既有结构的任何实质性干预等任务。提供既有资产调查、目的明确化、理想蓝图草图、差距规划、实证痛点识别以及使用全新的子智能体进行重新测试。防止并行标准、重复建设和流水线中断。

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Genogramm-Arbeit: Familien-Beziehungsmuster erkennen und reflektieren. Mehrgenerationen-Perspektive, Genogramm-Symbole, Muster-Erkennung und Ressourcen in der Familiengeschichte.

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。

Developer assistant (ATI successor). Provides a quick project overview via headless scan and routes to the available coding tools: CodeCommander MCP (analysis/refactor/diagnose) and the ellmos-code-tools module. Pure tool routing + scan, no own store.

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。

Plant Unterricht, Lernangebote und individuelle Förderung ohne Berichtsgenerator oder persönliche Vorlagen.

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。