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Implement and refactor frontend features using Vue and Quasar with repository architecture, theming, UX, and performance standards. Use when tasks involve components, composables, Pinia, routing, i18n/UI behavior, responsive layouts, or frontend clean architecture changes.
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Close out a completed workstream by updating README artifacts when needed, producing a commit message, and applying changelog-ready content when the work is ready for commit. Use after review when a stable checkpoint is ready.
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Base implementation skill for this repository across .NET/C#, backend APIs, database/ORM, frontend Vue/Quasar, and Rust with Clean Architecture rules. Use when the user asks to build features, fix bugs, refactor modules, or improve code-level performance, and use specialized skills as inheritance layers when available.
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Unit and integration testing strategy for create-vue-dsfr. Use for writing, updating, or refactoring Vitest specs and test coverage. Read the shared project skill before acting.
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Unit and integration testing strategy. USE FOR: writing tests; coverage improvements; vitest specs; test refactoring. DO NOT USE FOR: production code changes (use code-implementation skill); documentation (use documentation skill); commits (use commit-conventions skill).
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 developer behavioral profile and create Claude-discoverable artifacts
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Extract decisions, lessons, patterns, and surprises from completed phase artifacts
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Generate a comprehensive project summary from milestone artifacts for team onboarding and review
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Post-mortem investigation for failed GSD workflows — analyzes git history, artifacts, and state to diagnose what went wrong
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Detects and analyzes process injection techniques used by malware including classic DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading. Uses memory forensics, API monitoring, and behavioral analysis to identify injection artifacts. Activates for requests involving process injection detection, code injection analysis, hollowed process investigation, or in-memory threat detection.
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 NTLM relay attacks through Windows Security Event correlation by analyzing Event 4624 LogonType 3 for IP-to-hostname mismatches, identifying Responder/LLMNR poisoning artifacts, auditing SMB and LDAP signing enforcement across the domain, and detecting NTLM downgrade attacks from NTLMv2 to NTLMv1 using event log analysis.
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。
Parse Windows Prefetch files to determine program execution history including run counts, timestamps, and referenced files for forensic investigation.
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Examine file system slack space, MFT entries, USN journal, and alternate data streams to recover hidden data and reconstruct file activity on NTFS volumes.
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。
Captures and analyzes network packet data using Wireshark and tshark to identify malicious traffic patterns, diagnose protocol issues, extract artifacts, and support incident response investigations on authorized network segments.
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Analyzes indicators of compromise (IOCs) including IP addresses, domains, file hashes, URLs, and email artifacts to determine maliciousness confidence, campaign attribution, and blocking priority. Use when triaging IOCs from phishing emails, security alerts, or external threat feeds; enriching raw IOCs with multi-source intelligence; or making block/monitor/whitelist decisions. Activates for requests involving VirusTotal, AbuseIPDB, MalwareBazaar, MISP, or IOC enrichment pipelines.
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Detect sandbox evasion techniques in malware samples by analyzing timing checks, VM artifact queries, user interaction detection, and sleep inflation patterns from Cuckoo/AnyRun behavioral reports
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Investigate compromised Docker containers by analyzing images, layers, volumes, logs, and runtime artifacts to identify malicious activity and evidence.
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Rewrite AEM Edge Delivery Services page content for AI search discoverability (GEO — Generative Engine Optimization). Analyzes content structure, semantic clarity, and factual density, then produces optimized rewrites that rank in both traditional search and AI-powered search engines. Use when optimizing pages for search visibility, AI discoverability, or content clarity.
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Run a bounded red-green-refactor feedback loop only when the user explicitly requests TDD, accepts reproduction-first proof for a bug, or an accepted high-risk behavior specifically requires red/green evidence; do not trigger for every logic, bug, behavior, or implementation change.
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Generate, edit, inspect, or verify editable PowerPoint/PPTX decks when a .pptx file is the deliverable; use for template-preserving edits and from-scratch slide production, but not for HTML/SVG mockups, PDF-only reports, or presentation advice that needs no PPTX artifact.
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, edit, fix, or explain Mermaid diagrams for relationships, decision branches, interactions, lifecycles, and data models; also use when the parent selects a diagram to materially clarify an explanation. Do not trigger for simple status, one fact, short lists, quantitative charts, or marketing slides.
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Coverage review and verification sufficiency routing. Use when test coverage, uncovered paths, coverage reports, or verification adequacy need a read-only QA review; do not use for writing tests or running browser/E2E artifacts.
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Perform direct, bounded browser inspection through the `browser.qa` capability when the user requests runtime UI evidence or one browser-specific claim needs DOM/accessibility/console/network/visual verification; do not trigger for every UI change, backend work, delegated QA, or durable E2E artifact routing.
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。
Review comment, JSDoc, TODO, README, and docs-to-code factual consistency, stale or low-value comments, and Chinese comment/variable appropriateness; do not use for general code review, broad documentation rewrites, or auto-editing comments without approval.
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。