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概要と使いどころ
Wire CommunityToolkit.Mvvm ViewModels into Microsoft.Extensions.DependencyInjection. Covers the .NET Generic Host composition root, constructor injection, service lifetimes (Singleton / Transient / Scoped), IMessenger registration, resolving ViewModels in Views, keyed services, testing seams, and the legacy Ioc.Default escape hatch. Use across WPF, WinUI 3, .NET MAUI, Uno, and Avalonia.
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。
Manage DNS records for domains registered with Namecheap via their API. List domains, view/add/update/remove DNS host entries (A, AAAA, CNAME, MX, TXT, etc.), and guide users through API setup including public IP detection and credential configuration. Use when the user mentions Namecheap, DNS records, domain management, or wants to add/change/remove A records, CNAME records, MX records, or TXT records for their domains.
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。
Audit MCP (Model Context Protocol) server configurations for security issues. Use this skill when: - Reviewing .mcp.json files for security risks - Checking MCP server args for hardcoded secrets or shell injection patterns - Validating that MCP package-runner dependencies use exact reviewed versions, not bare names, @latest, or ranges - Detecting mutable npm/npx, bunx, pnpm dlx, yarn dlx, and npm exec references in MCP configurations - Auditing which MCP servers a project registers and whether they're on an approved list - Checking for environment variable usage vs. hardcoded credentials in MCP configs - Any request like "is my MCP config secure?", "audit my MCP servers", or "check .mcp.json" keywords: [mcp, security, audit, secrets, shell-injection, supply-chain, governance]
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。
Ranks any list of impediments and their countermeasures using a value-stream scoring model (ROI, Cost to Implement, Ease of Deployment, Risk Factor) and a fixed prioritization formula. Use when someone asks to prioritize, rank, sequence, or triage impediments, countermeasures, remediation items, risks, findings, gaps, action items, or backlog entries; or mentions value-stream prioritization, A3 / lean countermeasure ranking, ROI vs. effort scoring, or building a remediation / improvement backlog. Works with GHQR findings, audit results, retrospective action items, risk registers, architecture review gaps, or any free-form `{impediment, countermeasure}` list.
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 assemble the smallest compatible set of AI Agent Skills for an end-to-end natural-language goal. Use when a user wants Skills for a multi-step workflow, asks which Skills fit a project, needs an installed-Skill audit or conflict check, has low Skill recall, wants indirect helpers such as humanizers or compliance checks, or wants a project-specific Skill Stack with controlled installation. Search local Skills, registries, GitHub, and OpenCLI; compare adoption, verified fit, safety, and overlap. Do not use for locating one known or common Skill; use the generic find-skills workflow.
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。
Draft process letters and bid instructions for sell-side M&A processes. Covers initial indication of interest (IOI) instructions, final bid procedures, and management meeting logistics. Triggers on "process letter", "bid instructions", "IOI letter", "bid procedures", "final round letter", or "management meeting invite".
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 the SGLang kernels RFC when adding, moving, splitting, or reviewing kernel APIs, registry metadata, kernel tests, benchmarks, and model-specific implementations. Use with add-jit-kernel, add-sgl-kernel, and write-sglang-test for placement and migration checks.
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。
Guide for writing SGLang CI/UT tests. Covers CustomTestCase, CI registration, server fixtures, model selection, mock testing, and test placement. Always read test/README.md for the full CI layout, how to run tests, and extra tips. Use when creating new tests, adding CI test cases, writing unit tests, or when the user asks to add tests for SGLang features.
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 whenever the user needs ANY mailbox/email operation — checking, reading, searching, sending, replying, forwarding, organizing or deleting email, managing threads, connecting a personal mailbox, or registering a new mailbox. This skill is the single entry point for email tasks and orchestrates qwenpawmail-mcp for nine supported personal-mail domains.
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。
Re-encode verbose prose into a dense telegraphic register — punctuation as connectives, label frames, verbless assertions — without losing normativity or precision. Use when compressing system prompts, tool/function descriptions, skill bodies, or agent instructions; reducing token count or context bloat; making documentation token-efficient for LLM input; or rewriting text in compressed notation.
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。
Detect anomalies in Modbus/TCP and Modbus RTU industrial traffic via function code monitoring, register range validation, timing analysis, and deep packet inspection, using Zeek's Modbus analyzer, Suricata IDS with OT rules, and Python Markov chain models of normal transaction sequences. Use for deploying Modbus IDS in OT environments, baselining polling patterns, investigating suspicious Modbus traffic, or building function code allowlists.
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。
Discover and inventory shadow API endpoints that operate outside documented OpenAPI/Swagger specs, using traffic analysis against API gateways (Kong, AWS API Gateway, Envoy), cloud configuration scanning, and source code repository mining for undocumented routes. Use when assessing API attack surface, auditing for forgotten test environments or deprecated API versions still running, or building an API registration governance policy.
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。
Detect command injection against Modbus TCP/RTU in ICS/SCADA environments by monitoring unauthorized writes, anomalous function codes, malformed frames, and deviations from communication baselines using ICS-aware IDS and deep packet inspection. Use when deploying IDS for Modbus OT networks, investigating unauthorized PLC register/coil changes, or responding to FrostyGoop-style Modbus attacks.
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。
Systematically map and remove malware, backdoors, and attacker persistence mechanisms (registry Run keys, scheduled tasks, WMI subscriptions, services, cron/init.d) from infected Windows and Linux systems using Autoruns, EDR/AV, and YARA, restoring a clean state while preventing re-infection. Use after containment and forensic analysis have identified all compromised systems and persistence mechanisms and you are ready to eradicate and recover.
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。
Detect abuse of elevation control mechanisms (T1548), including Windows UAC bypass via auto-elevating binaries like fodhelper.exe and Linux sudo/setuid/setgid exploitation, by monitoring registry changes, integrity-level transitions, and parent-child process relationships via Sysmon and Windows Security events. Use when hunting privilege-escalation activity or validating elevation-abuse detection coverage.
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。
Flag misspelled, brandjacked, and typosquatted package names across npm, PyPI, and crates.io before installation, using edit-distance, keyboard-proximity, and known-target corpus matching with typomania, Microsoft OSSGadget's oss-find-squats, and pypi-scan. Use before adding a new dependency, as a CI/CD gate on pull requests, when reviewing an AI-generated ("slopsquatting") dependency list, or when auditing a lockfile diff for a swapped package.
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 and analyzes fileless malware that operates entirely in memory using PowerShell, WMI, .NET reflection, registry-resident payloads, and living-off-the-land binaries (LOLBins) without writing traditional executable files to disk. Use for requests involving fileless threat detection, in-memory malware investigation, LOLBin abuse analysis, or WMI persistence examination.
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 fileless malware and in-memory attacks that execute entirely in RAM without writing persistent files to disk, evading traditional antivirus. Use when building detections for PowerShell-based attacks, reflective DLL injection, WMI persistence, and registry-resident malware. Activates for requests involving fileless malware detection, in-memory attacks, PowerShell exploitation, or living-off-the-land techniques.
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。
Generate forensic super-timelines with Plaso's log2timeline.py, pinfo.py, psort.py, and psteal.py CLI tools (fusing file-system MACB, registry, EVTX, browser history, prefetch, LNK, and more), then triage and filter the results in Timesketch. Use when reconstructing the full sequence of events on a compromised or forensically imaged host during a DFIR 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。
Parses the Windows Amcache.hve registry hive with Eric Zimmerman's AmcacheParser and Timeline Explorer to extract evidence of program execution, application installation, and driver loading, including SHA-1 hash correlation with threat intel and timeline reconstruction. Use for Amcache forensics, program execution evidence gathering, or application compatibility cache investigations in DFIR work.
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 an automated adversary infrastructure tracking system in Python (dnspython, python-whois, shodan, networkx) that pivots across passive DNS, certificate transparency logs, WHOIS records, and IP enrichment to map threat-actor C2 networks and flag newly registered domains matching known patterns. Use when pivoting from known indicators to discover related C2 infrastructure or maintaining a continuously updated map of a threat actor's network.
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。
Generate domain permutations with dnstwist and check DNS resolution to detect typosquatting, homograph phishing, and brand impersonation domains registered against your organization. Use when asked to monitor for lookalike domains, investigate a phishing domain, or assess brand-impersonation risk.
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。
Detonate malware samples in Cuckoo Sandbox to observe runtime behavior — process creation, file system and registry changes, network communications, and API calls — and generate behavioral reports for classification and IOC extraction. Use when a sample has passed static triage and needs dynamic/behavioral analysis, when mapping a full infection chain, or when building YARA/behavioral signatures from observed sandbox activity.
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。
Strategic product leadership toolkit for Head of Product including OKR cascade generation, market analysis, vision setting, and team scaling. Use for strategic planning, goal alignment, competitive analysis, and organizational design.
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。