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Fetches canonical PR review state and renders derived state artifacts. Use when the user wants the state acquisition phase only (fetch, render, summarize) for a review-framework PR.

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。

Expert guidance for building modern Android UIs with Jetpack Compose, covering state management, navigation, performance, and Material Design 3.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for kernel attack surface, namespace and cgroup boundaries, container isolation assumptions, syscall paths, and escape primitive verification. Use when the user asks to analyze container-to-host escape paths, kernel exploit prerequisites, namespace crossover, capability misuse, or prove whether an exploit primitive crosses the sandbox boundary. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for LSASS-resident secrets, Windows logon sessions, Kerberos ticket caches, DPAPI-backed material, SSP artifacts, and replayable credential extraction. Use when the user asks to inspect LSASS memory, recover tickets or logon sessions, trace DPAPI or SSP material, distinguish which credential artifacts are replayable, or connect host-resident credential material to an accepted pivot or privilege edge. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Master memory forensics techniques including memory acquisition, process analysis, and artifact extraction using Volatility and related tools. Use when analyzing memory dumps, investigating incidents, or performing malware analysis from RAM captures.

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 self-serve acquisition and expansion motions. Use when deciding PLG vs sales-led, optimizing activation, driving freemium conversion, building growth equations, or recognizing when product complexity demands human touch. Includes the parallel test where sales-led won 10x on revenue.

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Setup and initialization guide for developing AWS CDK (Cloud Development Kit) applications in Python. This skill enables users to configure environment prerequisites, create new CDK projects, manage dependencies, and deploy to AWS.

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Install and configure the OpenViking long-term memory plugin for OpenClaw via natural conversation. Once installed, the plugin automatically captures facts from chats and recalls relevant context before each reply (auto-capture + auto-recall, cross-session). Covers prerequisites, install through OpenClaw's plugin manager (ov-install as backup), wizard-based configuration, slot activation, gateway restart, verification, multi-tenant root keys, multi-instance and uninstall. The user needs no CLI knowledge — the agent runs everything and only asks for a few values. Assumes the OpenViking server is already running; it does NOT install the server. Trigger on: "install OpenViking", "set up memory", "configure memory plugin", "add long-term memory", "semantic memory", "RAG", "帮我装 OpenViking", "配置记忆插件", "安装记忆功能", "接入 OpenViking".

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 accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms. Triggers on "merger model", "accretion dilution", "M&A model", "pro forma EPS", "merger consequences", or "deal impact analysis".

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Structure post-acquisition value creation plans with revenue, cost, and operational levers mapped to an EBITDA bridge. Includes 100-day priorities, KPI targets, and accountability frameworks. Use when planning post-close execution, preparing operating partner materials, or building a board-ready value creation roadmap. Triggers on "value creation plan", "100-day plan", "post-close plan", "EBITDA bridge", "operating plan", or "value creation levers".

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Create institutional-quality equity research initiation reports through a 5-task workflow. Tasks must be executed individually with verified prerequisites - (1) company research, (2) financial modeling, (3) valuation analysis, (4) chart generation, (5) final report assembly. Each task produces specific deliverables (markdown docs, Excel models, charts, or DOCX reports). Tasks 3-5 have dependencies on earlier tasks.

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。

This skill covers detecting cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.

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。

Respond to security incidents in AWS, Azure, and GCP via identity-based containment, cloud-native log analysis (CloudTrail, Azure Activity Logs, GCP Audit Logs), resource isolation, and forensic evidence acquisition adapted for ephemeral cloud infrastructure. Use when CSPM alerts or audit logs show compromised cloud credentials, unauthorized IAM changes, or a breach spanning cloud services.

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。

Drive the AADInternals PowerShell toolkit to perform Microsoft Entra ID tenant reconnaissance, access-token acquisition across Microsoft APIs, and federation/AD FS backdoor testing (Golden SAML, T1606.002) for defensive validation. Use during an authorized Entra ID/Microsoft 365 red-team assessment to map external attack surface or verify AD FS signing certs resist Golden SAML.

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。

Performs Linux memory acquisition using LiME (Linux Memory Extractor) kernel module and analysis with Volatility 3 framework. Extracts process lists, network connections, bash history, loaded kernel modules, and injected code from Linux memory images. Use when performing incident response on compromised Linux systems.

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。

HeroUI Native component library for React Native (Tailwind v4 via Uniwind). Use when building mobile UIs with HeroUI Native — creating Buttons, Cards, TextFields, Dialogs; installing heroui-native; configuring dark/light themes; or fetching component docs. Keywords: HeroUI Native, heroui-native, React Native UI, Uniwind, mobile components.

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。

HeroUI v3 React component library (Tailwind CSS v4 + React Aria). Use when building UIs with HeroUI — creating Buttons, Modals, Forms, Cards; installing @heroui/react; configuring dark/light themes with oklch variables; or fetching component docs. Keywords: HeroUI, Hero UI, heroui, @heroui/react, @heroui/styles.

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 a TYPED citation/reference graph over an ingested corpus — not just embeddings. Flat similarity retrieval cannot tell you that document A *overrules* B, *distinguishes* C, or *relies_on* D. This skill extracts every inter-document reference, classifies the edge TYPE with LLM judgment, and writes first-class typed edges via `gbrain link`, so `gbrain graph-query --type` can walk the argument ("everything this brief relies on, minus anything overruled since"). Every cite-heavy corpus is the same shape: law, academic papers, patents, regulatory filings, a book's bibliography.

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。

Open the GBrain owner dashboard, manage MCP clients and permissions, or connect a native OAuth harness. Distinguishes owner administration from ordinary MCP access.

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 writing or debugging integration tests for error processors in packages/core/src/processors/. Covers the MockLanguageModelV2 pattern for simulating API errors and verifying retry behavior, plus the build prerequisites for focused vitest runs.

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。

Add or debug Table v9 features: registration, row-model slots, prerequisites, sorting, filtering, pagination, selection, spanning, and column layout. Read only task-relevant feature references.

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。

/cs:gdpr-audit-prep <scope> — GDPR audit 6-question Article-cited forcing interrogation. Use before annual internal GDPR review, post-breach internal audit, DPA investigation readiness, or acquisition due diligence.

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Use when a Head of People Ops, BizOps lead, or Internal Communications owner needs to draft and sequence an internal-only change-management communication — a re-org announcement, a tool rollout, a policy change, a leadership transition, a layoff, an acquisition close, or an internal product launch — and the audience is employees (not customers). Pairs Prosci ADKAR and Kotter's 8-step change model with deterministic stdlib-only Python tools to produce a sequenced touchpoint calendar, a Kotter-compliant primary announcement, an audience-segmented FAQ, and manager cascade talking points; industry-tuned via --profile {tech-startup, scaleup, enterprise, public-company, non-profit}. Triggers on "all-hands announcement", "change comms", "rollout comms", "re-org announcement", "manager talking points", "layoff comms".

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。

**MANDATORY prerequisite** — you MUST invoke this skill BEFORE every `use_figma` tool call. NEVER call `use_figma` directly without loading this skill first. Skipping it causes common, hard-to-debug failures. Trigger whenever the user wants to perform a write action or a unique read action that requires JavaScript execution in the Figma file context — e.g. create/edit/delete nodes, set up variables or tokens, build components and variants, modify auto-layout or fills, bind variables to properties, or inspect file structure programmatically.

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。