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概要と使いどころ
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.
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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。
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.
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 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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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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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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Simplify a bounded code area when the user explicitly requests behavior-preserving refactoring or a named complexity/readability problem is the accepted task; do not trigger automatically after implementation, during every review, for adjacent cleanup, or when behavior may change.
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Conduct one bounded evidence-grounded code review when the user explicitly requests review or ROSE names a concrete unresolved correctness/quality risk; do not trigger automatically after implementation, before every merge, for every bug fix/refactor, or as a completion gate.
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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.
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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.
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Run a non-destructive open-source, npm, or public release readiness checklist covering package metadata, provenance, license, internal artifact exposure, and dry-run evidence; complements security, shipping, and sanitizer reviews, and must not publish, delete, rewrite history, or mutate release state.
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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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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.
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Idiomatic Go - package and interface design, error wrapping, table-driven tests, generics, the modern standard library (slices/maps/cmp/errors.Join), current syntax, and logging discipline. Use when writing, reviewing, or refactoring any Go code, especially code drifting toward Java/Spring shapes (deep layer trees, generic repositories, heavy frameworks) - even if the user never says "idiomatic". Distilled from spf13/go-skills and adapted to this repo.
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Scores and prioritizes technical debt by impact, risk, and effort. Provides ranked backlog with ROI analysis and quarterly paydown recommendations. Use for "tech debt", "technical debt management", "code quality", or "refactoring priorities".
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Creates comprehensive post-incident documents with timeline, root cause analysis, contributing factors, action items, and ownership. Follows SRE best practices for blameless postmortems. Use for "postmortem", "incident review", "RCA", or "post-incident".
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Identifies domain modules, ownership boundaries, dependencies, and interfaces using Domain-Driven Design principles. Provides domain maps, bounded contexts, refactor recommendations. Use for "DDD", "domain modeling", "bounded contexts", or "service boundaries".
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Creates comprehensive GitHub Actions CI/CD workflows for linting, testing, building, and deploying. Includes caching strategies, matrix builds, artifact handling, and failure diagnostics. Use for "GitHub Actions", "CI pipeline", "workflow automation", or "continuous integration".
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Generates deterministic seed data for development and testing with factory functions, realistic fixtures, and database reset scripts. Use for "data seeding", "test fixtures", "database seeding", or "mock data generation".
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You are helping a penetration tester bypass two-factor authentication. The
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。