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概要と使いどころ
Writes SEO-optimized content based on provided keywords and topic briefs. Creates engaging, comprehensive content following best practices. Use PROACTIVELY for content creation 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。
Creates optimized meta titles, descriptions, and URL suggestions based on character limits and best practices. Generates compelling, keyword-rich metadata. Use PROACTIVELY for new content.
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 provided content for quality, E-E-A-T signals, and SEO best practices. Scores content and provides improvement recommendations based on established guidelines. Use PROACTIVELY for content review.
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 keyword usage in provided content, calculates density, suggests semantic variations and LSI keywords based on the topic. Prevents over-optimization. Use PROACTIVELY for content optimization.
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。
Create LangGraph-based agent with modern patterns
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。
.NET testing fundamentals overview and navigation center. Triggered when users ask about "how to write .NET tests", ".NET testing getting started", "required testing tools", "testing best practices", "learn testing from scratch", and other general testing needs. Recommends appropriate sub-skills based on specific requirements, covering testing fundamentals, test data, assertions, mocking, special scenarios, and other 19 fundamental skills. Keywords: dotnet testing, .NET testing, testing getting started, how to write tests, testing best practices, unit test, unit test, xunit, 3A pattern, FIRST principle, assertion, assertion, mock, stub, NSubstitute, test data, AutoFixture, Bogus, validator, FluentValidation, TimeProvider, IFileSystem, code coverage, ITestOutputHelper, test naming
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。
.NET advanced testing skills overview and navigation center. Triggered when users ask about "integration testing", "API testing", "containerized testing", "microservice testing", "test framework migration", "Testcontainers", "Aspire testing", and other advanced testing needs. Recommends appropriate sub-skills based on specific requirements, covering integration testing, Testcontainers, Aspire testing, framework upgrades, and other 8 advanced skills. Keywords: integration testing, integration testing, API testing, advanced testing, advanced testing, testcontainers, aspire testing, WebApplicationFactory, TestServer, database test, database testing, EF Core test, MongoDB test, Redis test, Docker test, container testing, microservice test, microservice testing, .NET Aspire, xUnit upgrade, TUnit, framework migration
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-powered skill recommendation engine for dotnet-harness. Analyzes project context and recommends relevant skills based on detected frameworks, packages, and patterns. Triggers on: recommend skill, suggest skills, what skill should I use, skill suggestion, project analysis recommendation.
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-powered skill recommendation engine for dotnet-agent-harness. Analyzes project context and recommends relevant skills based on detected frameworks, packages, and patterns. Triggers on: recommend skill, suggest skills, what skill should I use, skill suggestion, project analysis recommendation.
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 and remediate dependency/package vulnerabilities across .NET backend, frontend (npm/pnpm/yarn), and Rust projects with severity-based quality gates. Use when the user asks for SCA checks, dependency hardening, or release security gates.
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 and remediate dependency/package vulnerabilities across .NET backend, frontend (npm/pnpm/yarn), and Rust projects with severity-based quality gates. Use when the user asks for SCA checks, dependency hardening, or release security gates before build/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。
Execute all plans in a phase with wave-based parallelization
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 tests for a completed phase based on UAT criteria and implementation
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。
Gather phase context through adaptive questioning before planning. Use --auto to skip interactive questions (the agent picks recommended defaults). Use --chain for interactive discuss followed by automatic plan+execute. Use --power for bulk question generation into a file-based UI (answer at your own pace).
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。
Evaluates and selects Threat Intelligence Platform (TIP) products based on organizational requirements including feed integration capability, STIX/TAXII support, workflow automation, analyst interface, and total cost of ownership. Use when conducting a TIP procurement, migrating between TIP solutions, or assessing whether the current TIP meets program maturity requirements. Activates for requests involving ThreatConnect, MISP, OpenCTI, Anomali, EclecticIQ, or TIP procurement 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。
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.
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。
Tests and exploits deep link (URL scheme and App Link) vulnerabilities in Android and iOS mobile applications to identify unauthorized access, data injection, intent hijacking, and redirect manipulation. Use when assessing mobile app attack surface through custom URI schemes, Android App Links, iOS Universal Links, or intent-based navigation. Activates for requests involving deep link security testing, URL scheme exploitation, mobile intent abuse, or link hijacking.
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。
Executes authorized phishing simulation campaigns to assess an organization's susceptibility to email-based social engineering attacks. The tester designs realistic phishing scenarios, builds credential harvesting infrastructure, sends targeted phishing emails, and tracks open rates, click-through rates, and credential submission rates to measure human security awareness. Activates for requests involving phishing simulation, social engineering assessment, email security testing, or security awareness measurement.
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。
BloodHound is a graph-based Active Directory reconnaissance tool that uses graph theory to reveal hidden and unintended relationships within AD environments. Red teams use BloodHound to identify attac
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。
Detect network reconnaissance and port scanning using Suricata and Snort IDS signatures, threshold-based detection rules, and traffic anomaly analysis to identify Nmap, Masscan, and custom scanning 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。
Detects ransomware encryption activity in real time using entropy analysis, file system I/O monitoring, and behavioral heuristics. Identifies mass file modification patterns, abnormal entropy spikes in written data, and suspicious process behavior characteristic of ransomware encryption routines. Activates for requests involving ransomware behavioral detection, entropy-based file monitoring, I/O anomaly detection, or real-time encryption activity alerting.
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 anomalies in Modbus/TCP and Modbus RTU communications in industrial control systems. It addresses function code monitoring, register range validation, timing analysis, unauthorized client detection, and deep packet inspection for malformed Modbus frames. The skill leverages Zeek with Modbus protocol analyzers, Suricata IDS with OT rules, and custom Python-based detection using Markov chain models for normal Modbus transaction sequences.
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 DNS-based data exfiltration by analyzing Zeek dns.log for high-entropy subdomains and anomalous query patterns
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。