1.5万 件 ・ 関連度順
概要と使いどころ
"Apply the Capital Asset Pricing Model (CAPM) to estimate expected returns and assess risk-return tradeoffs. Use this skill when the user needs to calculate expected return on an asset, interpret beta as systematic risk exposure, evaluate whether an investment compensates for risk, or when they ask 'what return should I expect', 'what is the risk premium', or 'how does beta affect pricing'.".
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。
"Apply organizational ambidexterity theory to balance exploration and exploitation activities. Use this skill when the user needs to diagnose whether an organization is over-exploiting or over-exploring, design structures that support both innovation and efficiency, or evaluate the tension between short-term performance and long-term renewal.".
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。
Post-exploitation workflow. Covers privilege escalation (Linux SUID/sudo/kernel, Windows UAC/service/token), persistence assessment, local enumeration, credential harvesting, and pivot preparation. Structured workflows for Linux and Windows targets using impacket, netexec, john, linpeas/winpeas, and standard Kali tools. Includes kernel exploit reference tables, GTFOBins exploitation chains, Potato attack selection, Docker/container escapes, DLL hijacking, SSH key harvesting, credential recovery from memory, and Windows token manipulation. Chains from /pentester or /credential-audit when access is obtained.
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 insecure platform interaction in mobile apps (Android/iOS). Trigger on: exported Activity, exported Service, exported BroadcastReceiver, Content Provider, Intent injection, deep link hijacking, WebView JavaScript enabled, JavascriptInterface, addJavascriptInterface, setJavaScriptEnabled, intent:// scheme, file:// scheme, WKWebView, WKScriptMessageHandler, UIPasteboard, URL scheme hijacking, Universal Links, PendingIntent, FLAG_IMMUTABLE, overlay attack, tapjacking, screenshot prevention, FLAG_SECURE, Broadcast sniffing, IPC data exposure. Covers MASVS-PLATFORM-1/2/3.
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。
Test Model Context Protocol (MCP) servers and tool-calling systems for security vulnerabilities including tool injection, parameter manipulation, privilege escalation, and data exfiltration through AI agent tool interfaces. Use this skill when assessing MCP server implementations, AI agent tool integrations, or any system that exposes tools to language models. Covers tool confusion attacks, cross-tool exploitation, and MCP server hardening assessment.
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。
Cloud security posture assessment for AWS, Azure, and GCP. Tests IAM privilege escalation paths, public storage exposure, serverless attack surface, database exposure, logging gaps, container registry security, and cloud-specific attacks. Both authenticated (with cloud credentials) and unauthenticated (external) modes. Uses nuclei cloud templates, Prowler, ScoutSuite, manual IMDS/metadata probing, and deep AWS/Azure/GCP CLI enumeration. Produces: cloud architecture diagram, attack path map, findings per category, compliance mapping (SOC 2, PCI DSS 4.0, HIPAA, CIS), PoCs for confirmed exploits. Chains into /gh-export for issue filing.
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。
AI/LLM red-team assessment using the OWASP LLM Top 10 (2025) + OWASP AI Testing Guide (AITG v1, Nov 2025) frameworks, plus OWASP MCP Top 10 runtime testing for agentic/MCP targets. Tests prompt injection, jailbreaks, system prompt leakage, sensitive data extraction, excessive agency, improper output handling, model extraction, content bias, evasion, membership inference, MCP token exposure, MCP command injection, and more. Uses four tools in combination: FuzzyAI (single-turn jailbreak fuzzing), PyRIT (multi-turn orchestrated attacks), Garak (probe-based vulnerability scanning), and promptfoo (plugin-based red-team evaluation). Each tool covers different OWASP categories; running them together gives systematic coverage. Includes a conditional MCP reconnaissance phase and a post-access AI infrastructure phase (chained from /post-exploit). Produces: OWASP LLM Top 10 + AITG + MCP coverage matrix, findings per category, architecture diagram of the AI system, PoCs for confirmed exploits. Chains into /gh-export for issue filing.
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。
Phase 1 of the feature-pipeline suite — stress-test a CLI command, feature, flag, or module as a developer seeing it for the first time, then file GitHub issues for every distinct finding. Use when someone says "explore X", "test X", "find issues with X", "what's wrong with X", or after /feature-pipeline init. Also triggers standalone as /fp-explore <feature> when you want just the exploration phase without the full pipeline. Reads the target feature from .fp-state.json (or the argument if provided). Completes in one bounded turn and prints the M1 stop hook so the user decides whether to continue to /fp-plan.
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 ENCODE experiments locally with publications, citations, and provenance. Use when the user wants to build a collection of experiments, manage citations, compare experiments, or track data provenance.
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。
Explains complex code through clear narratives, visual diagrams, and step-by-step breakdowns. Use when user asks to explain code, understand algorithms, analyze design patterns, wants code walkthroughs, or mentions "explain this code", "how does this work", "code breakdown", or "understand this function".
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。
Rapid UI prototyping — generates 3 visually distinct HTML/CSS components from a text prompt and serves them in a live browser gallery. Use when user runs /prototype, asks to "prototype a UI", "mock up a component", "generate HTML mockups", "create UI variations", "design exploration", "quick UI concept", or wants to see multiple visual approaches to a component. Also trigger when user says "show me different ways to build...", "explore different designs for...", or wants rapid visual exploration of a UI idea — even without saying "prototype" explicitly.
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。
Standalone E-E-A-T scoring rubric for a URL or content draft. Scores Experience, Expertise, Authoritativeness, and Trust 0-5 each using concrete detectable signals, framed per Google's creating-helpful-content doc. Use when user says "E-E-A-T", "EEAT", "experience expertise", "trust signals", or "author authority".
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 evaluate paid-ad experiments with hypotheses, randomization units, sample-size and duration assumptions, guardrails, platform experiment tools, analysis, and decision rules. Use for A/B test, split test, experiment design, hypothesis, statistical significance, sample size, test duration, or experiment readout.
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 this skill when designing the UX and content strategy for a Salesforce-powered self-service portal or help center — pre-deflection article surfacing, Help Center search UX, friction-calibrated case submission forms, community peer support layers, and deflection measurement. Trigger keywords: design self-service portal, case deflection strategy, help center UX design, reduce support volume with self-service, knowledge base search experience. NOT for picking which contact reasons to deflect and through which channel — use architect/case-deflection-strategy. NOT for building the Experience Cloud site itself — use admin/experience-cloud-site-setup. More trigger keywords: article visibility matrix IsVisibleInCsp IsVisibleInPkb, which articles show in the customer portal, case visibility for portal users, CaseComment IsPublished customer visible comment, self-registration profile and account for a portal, Help Center template does not support login, deflection metrics SOQL KnowledgeArticleViewStat, self-service journey map, moderation policy for a support community.
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。
Automating post-sandbox-refresh cleanup via the `SandboxPostCopy` interface — the Apex class that runs ONCE after a sandbox refresh or clone completes, before users can log in. Used to mask emails, deactivate users, scrub integration endpoints, disable scheduled jobs, and reapply per-environment configuration the metadata copy doesn't carry. Covers the interface contract (`runApexClass` setting, `SandboxContext` parameter, single-execution semantics), the email-masking pattern that stops sandbox tests emailing production addresses, and the refresh runbook checklist. NOT for choosing sandbox type or refresh cadence — use admin/sandbox-strategy. NOT for re-seeding reference data after a refresh — use data/sandbox-refresh-data-strategies. Trigger keywords: SandboxPostCopy, runApexClass, SandboxContext, Test.testSandboxPostCopyScript, RunAsAutoProcUser, Automated Process user, CronTrigger, System.abortJob, sandbox email masking, post-refresh runbook.
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 planning, sequencing, or troubleshooting an org-wide migration from Salesforce Classic to Lightning Experience. Covers the LEX Transition Assistant Readiness Check, asset triage matrix (Visualforce, JavaScript buttons, page layouts, Knowledge, email templates, list views, AppExchange), pilot/wave rollout sequencing, end-user adoption telemetry, and cutover criteria. Triggers: 'lightning experience transition', 'classic to lightning migration plan', 'LEX readiness check', 'why are some users still on Classic', 'turning on Lightning for everyone'. NOT for individual asset migrations like a single VF page (use lwc/visualforce-to-lwc-migration), a single JavaScript button (use admin/custom-button-to-action-migration), or Knowledge article migration (use admin/knowledge-classic-to-lightning) — this skill orchestrates the program. NOT for Lightning App Builder page design (use admin/lightning-app-builder-advanced).
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 a Lightning record page, home page, or app page is slow to load or render — covers Experienced Page Time (EPT) analysis, component count reduction, progressive disclosure via tabs and conditional rendering, Lightning Experience Insights diagnostics, and DOM/XHR minimization strategies. Triggers: 'Lightning page is slow', 'EPT is high', 'record page takes too long to load', 'too many components on page', 'Lightning Experience Insights shows slow page', 'how to optimize Lightning page performance'. NOT for Visualforce page performance (separate concern). NOT for Apex or SOQL query optimization (use apex/apex-cpu-and-heap-optimization or data/soql-query-optimization). NOT for report or dashboard performance (use admin/report-performance-tuning).
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 the engagement model for an Experience Cloud community: reputation levels, ideation, and content contribution strategy. Triggers: 'community engagement strategy', 'gamification Experience Cloud', 'reputation levels setup', 'ideation community portal', 'member recognition program'. NOT for blocking, flagging or approving what members post — use admin/experience-cloud-moderation. NOT for measuring logins, page views or engagement after launch — use data/community-analytics-data. Also covers: the Network reputation elements that carry the ladder (enableReputation, reputationLevels/level/label/lowerThreshold, reputationPointsRules/pointsRule/eventType/points), the 16 documented reputation eventType values and their default points, ManagedTopics / ManagedTopic (Navigational vs Featured, position 0-24), NetworkMember.ReputationPoints seeding, and why FeedItem cannot carry the engagement dashboard.
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。
Ideate a brand-new game concept with the user, from a blank page or a one-line hint to a finished CONCEPT card. Use it whenever the user wants to come up with a new game — whether the project has no design document yet, or already has one and they're exploring a fresh idea. Through a structured divergence/convergence dialogue it explores ideas, frames the hook, generates and scores concepts (market validation delegated to /unikit-gd-explore), and settles pillars, loops, motivation, and a pre-mortem. Trigger whenever the user wants to make or invent a game, doesn't know where to start, or gives a genre/theme hint, e.g. "let's come up with a game", "I don't know what game to make", "I want to make a roguelike", "a game about zombies", "a farming game", "help me come up with a concept". For researching or dissecting existing games use /unikit-gd-explore; to write an already-chosen concept as the master GDD use /unikit-gd-spec.
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 and ideation partner for GAME DESIGN — think through design ideas before writing them into the GDD; produces a brief, never edits the GDD itself. Use to assess a genre or market for viability, dissect a reference game (mechanics → dynamics → aesthetics), explore how to improve or extend an existing system, flow, or content type, research new mechanics the design lacks, investigate a part of the GDD in code, or develop the research bucket of a /unikit-gd-review report into decided edits. Trigger on "explore how to improve the flow", "ways to improve the combat system", "is this genre saturated", "break down the combat of Hades", "work out the review's open questions". GAME-DESIGN research only — for CODE or technical research use /unikit-explore; to reconstruct a design from code use /unikit-gd-recon; to write a change into the GDD use /unikit-gd-system or /unikit-gd-spec; to apply edits you know use /unikit-gd-apply; to invent a new game use /unikit-gd-brainstorm.
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。
Разработка прошивок для BE-U1000 (Baikal Electronics / Байкал Электроникс, три ядра RISC-V: BR-350 и BM-310) на отладочных платах EVU-BA-2.1, EVU-BA-2.0 и EVU-BA-1.2 — её eFlash и QSPI flash, UART0/BootROM CLI, PWMA (захват и импульсы), АЦП с DMA, CAN FD, SPI, WDT, CLIC, а также SDK Байкала и его система сборки на make. Use when working on this board or any BE-U1000 / BMCU_U project (SDK 2.1/2.3, riscv32-none-elf, dfu-util, OpenOCD): настройка проекта, Makefile и MEM_REG_ROM, карта выводов и разъёмы XP1/XP8/XP9/XP10, режимы начальной загрузки и страповые выводы, прошивка по UART XMODEM либо USB DFU, работа с eFlash и TCM, прерывания и CLIC, отладка по JTAG — и разбор, почему плата молчит, не стартует, зависает или почему периферия «настроилась», а обмена нет.
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。
Auto-assembles a domain-specific expert panel (7–10 experts), scores any content or strategy artifact against a typed rubric, and iterates until the aggregate hits 90+ (max 3 rounds). Use as a quality gate on copy, email sequences, landing-page drafts, strategy docs, charts, titles, or recruiting evaluations — or when another skill needs a final review gate on its output. Triggers on "expert panel this", "score this", "rate these variants", "quality check this", "panel review", "expert score", "evaluate this copy/strategy/page". For variant generation and multi-round conversion optimization see autoresearch; for live-URL CRO auditing see conversion-ops; for the scripted content-production pipeline see content-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。
Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports both Anthropic's claude CLI and OpenAI's codex CLI as agent harnesses (selected via --harness).
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。
Launch Marcus multi-agent experiments with independent CLI agents in tmux panes. Use when the user says "build X with Marcus", "run a Marcus experiment", "spawn N agents with Marcus", "/marcus", or references the Marcus multi-agent framework. This skill handles experiment setup, config generation, and spawning independent agent CLI processes that coordinate via the Marcus MCP server. Each agent runs in its own tmux pane with full autonomy. NOT for ClawTeam — this is specifically for the Marcus MCP-based multi-agent system. NOTE: "Marcus" is also the name of the MCP server that agents use for coordination. The /marcus skill launches experiments that USE the Marcus MCP server — they are complementary, not competing. The MCP server must be running before invoking this skill. The Marcus MCP server is agent-agnostic; this skill supports Anthropic's claude CLI, OpenAI's codex CLI, and Google's gemini CLI as agent harnesses (selected via --harness).
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。