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概要と使いどころ
Master software architect specializing in modern architecture patterns, clean architecture, microservices, event-driven systems, and DDD. Reviews system designs and code changes for architectural integrity, scalability, and maintainability. Use PROACTIVELY for architectural decisions.
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Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.
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Create AI avatar and talking head videos with OmniHuman, Fabric, PixVerse via inference.sh CLI. Models: OmniHuman 1.5, OmniHuman 1.0, Fabric 1.0, PixVerse Lipsync. Capabilities: audio-driven avatars, lipsync videos, talking head generation, virtual presenters. Use for: AI presenters, expla...
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Build automated AI workflows combining multiple models and services. Patterns: batch processing, scheduled tasks, event-driven pipelines, agent loops. Tools: inference.sh CLI, bash scripting, Python SDK, webhook integration. Use for: content automation, data processing, monitoring, schedul...
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Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.
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Plan, run, and measure an adversary engagement operation using the MITRE Engage framework so that deployed deception is driven by strategy instead of deployed ad hoc. Covers the Engage Matrix (Prepare, Expose, Affect, Elicit, Understand), the 10-Step Operational Process, mapping engagement Activities to the ATT&CK techniques they expose, and defining measurable Goals and Operational Objectives. Use when a team has honeypots, honeytokens, or canary tokens but no coordinating strategy, when leadership asks "should we engage attackers and how", when building a deception/denial program, when writing an adversary engagement operation plan, or when deciding which deception Activities to deploy against a specific threat actor. Keywords: MITRE Engage, adversary engagement, cyber deception strategy, denial and deception, Engage Matrix, EAC, EGO, Expose Affect Elicit, deception program, honeypot strategy, engagement operation.
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Create or update feature specifications from natural language descriptions. Use when starting new features or refining requirements. Generates spec.md with user stories, functional requirements, and acceptance criteria following spec-driven development methodology.
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Run a live investigation as an operator-driven query loop: the operator runs each query on the live system and pastes the result back, and you guide the investigation one labelled query at a time. Use alongside support-assist (which covers what to investigate) whenever someone is pasting query or command output back from a deployment, especially during an incident. Covers labelling, pacing, making each query decide the next step, version-grounding, and keeping queries cheap and correctly classified.
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E2B Desktop Sandbox with autonomous computer use — cloud Linux environments for browser automation, visual UI grounding, screenshot analysis, and shell execution. Supports Browser Use cloud sessions, Playwright integration, and LLM-driven desktop control. Use when asked about sandboxes, computer use, browser automation, E2B, desktop control, visual testing, or cloud Linux environments.
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Computer Use Agent — autonomous browser control via Steel, Browser Use, and Browserbase cloud providers. Supports headful CDP sessions, CAPTCHA solving, proxy rotation, live view, session recording/replay, Playwright/Puppeteer integration, and LLM-driven visual browsing. Use when asked about computer use, browser automation, web scraping, Steel sessions, cloud browsers, headful browsing, CAPTCHA solving, or autonomous web navigation.
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Playwright-powered browser automation and E2E testing for SolanaOS Hub. Covers test configuration, agent-driven test generation (planner/generator/healer), NanoHub route testing, Convex API validation, wallet flow testing, IPFS Hub verification, and CI/CD integration. Use when asked about E2E tests, browser automation, Playwright setup, NanoHub testing, visual regression, or Hub route verification.
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Test-driven development with red-green-refactor and behavior-focused tests. Use when the user explicitly wants test-first work, a regression test before a fix, or integration tests that drive a feature through a public interface.
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Comprehensive data science workflow skill for analyzing tabular and time series data. Use when conducting exploratory data analysis, building predictive models, performing feature engineering, or generating data-driven insights. Supports end-to-end analysis from data understanding through model deployment, following industry best practices for regression, classification, time series forecasting, and statistical analysis.
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Comprehensive, measurement-driven performance optimization for latency, throughput, memory/GC, and tail behavior. Use when the user asks to optimize/speed up, reduce latency (p95/p99), increase throughput/QPS, lower CPU/memory/allocations/GC pauses, profile hot paths, or run a benchmarked perf pass (including JSONL/query-heavy code). Requires before/after measurement on a runnable workload (or an explicit `UNMEASURED` plan) plus a correctness gate.
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Load for native CQS commands, queries, immutable request/result contracts, handlers (ICommandHandler, IQueryHandler), validators, cache invalidation, idempotency, or specification-driven reads in Explore.Application; not for controller-only or repository-only edits.
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Orchestrate iOS screenshot automation with xcodebuild/simctl for build-run, AXe for UI actions, JSON settings and plan files, Koubou-based framing (`asc screenshots frame`), and screenshot upload (`asc screenshots upload`). Use when users ask for automated screenshot capture, AXe-driven simulator flows, frame composition, or screenshot-to-upload pipelines.
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Implement one scoped slice using TDD red-green-refactor. Use when ready to write code for a defined slice of work, or when the user wants test-driven development.
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Knowledge base from NASA-STD-8729.1A — NASA's R&M (Reliability and Maintainability) standard covering spaceflight and support systems (Revision A, 2017-06-13). Use for NASA's objectives-driven R&M framework — the R&M objectives hierarchy (one Top Objective decomposed into four sub-objectives, paired with tailorable strategies), how R&M requirements are established inside the SMA Plan required by NPR 7120.5, the SMA Technical Authority concurrence/independent-evaluation governance, milestone vs. readiness review gates, the reliability/maintainability/availability vocabulary (Ai vs. Ao, the failure causal chain, risk as a triplet), and the R&M Evidentiary Methods catalogue (FMEA/FMECA, FTA, RBDA, RCM, LORA, plus the space-environment and parts-pedigree analyses). Scoped to NASA spaceflight and support systems and to assurance planning: it is an objectives-and-strategies standard, so it deliberately does NOT prescribe step-by-step analysis procedures (those live in the referenced NASA Preferred Reliability Practices) and is thin on facility R&M, detailed math/derivations, and non-NASA or commercial life cycles.
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Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.
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Knowledge base from NASA NPR 7150.2D — NASA Software Engineering Requirements. Use for NASA's Agency-wide software-engineering requirements: the software classification scheme (Classes A–F), the Requirements Mapping Matrix and class-driven applicability, tailoring and Technical Authority governance, the SWE-### 'shall' requirements across software management (Ch 3) and the engineering life cycle (Ch 4), the supporting disciplines (configuration management, risk, peer reviews/inspections, measurement, non-conformance — Ch 5), safety-critical and cybersecurity requirements, IV&V applicability, traceability, and the Appendix A definitions. Does not cover detailed software-assurance/safety procedures (see NASA-STD-8739.8), implementation how-to and document content (see NASA-HDBK-2203), the systems-engineering process framework (see NPR 7123.1), or program/project management (see NPR 7120.5).
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Knowledge base from the FAA Requirements Engineering Management Handbook (DOT/FAA/AR-08/32). Use for writing requirements for real-time, embedded control systems — the avionics/medical slant — via the Handbook's eleven recommended practices: system overview and boundary (monitored/controlled variables), operational concepts (use cases), environmental assumptions, change-tolerant functional architecture (dependency diagrams), safety-driven architecture revision (FHA/PSSA/fault tree), system modes, detailed behavior and performance requirements (ideal value + tolerance + latency), the four-variable model bridge to software requirements (MON/CON/NAT/REQ, IN'/REQ'/OUT', DO-178B mapping), subsystem allocation, and rationale. Carries the Isolette Thermostat and Flight Control System worked examples. Slanted toward control systems with sensors and actuators; thin on information-system / enterprise / agile requirements, on requirements-management tooling, and on the formal-methods internals of SCR/RSML/SpecTRM (it names them, does not re-teach them). Does not reproduce the IEEE/DO-178B/ARP standards it cites.
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Knowledge base from the DoD Systems Engineering Guidebook (OUSD R&E, February 2022). Use for the DoD SE process model — the 16 SE processes (8 technical management + 8 technical) mapped to ISO/IEC/IEEE 15288, the event-driven technical reviews and audits across the Major Capability Acquisition life cycle (ASR, SRR, SFR, PDR, CDR, SVR/FCA, PRR, PCA), the Systems Engineering Plan (SEP), risk/issue/opportunity management, TPMs and leading indicators, system-of-systems and digital engineering, and the 24 design considerations (RAM, system safety, HSI, system security engineering, MOSA, supportability, etc.). Acquisition-program oriented: thin on detailed cost estimating, contracting law, and non-DoD or commercial life cycles.
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Erkennt Nutzeraufträge der Form "hole aus einem Ordner immer bestimmte Dateien und sammle sie an einem Ziel" und richtet dafür das Modul file-collect-sort-action (CLI fcsa) ein — ein konfigurationsgetriebener Agent, der Ordner scannt, Dateien per Schablone kategorisiert und gestufte Aktionen anwendet (move/copy/duplicate-check/delete/OCR/place-information). Nutze diesen Skill bei Sätzen wie "hole aus <Ordner> immer <Dateiart> und sammle sie in <Ziel>", "sortiere den Ordner X automatisch nach ...", "sammle eingehende Dateien aus ... in ...", "räume diesen Ordner regelbasiert auf" oder "verschiebe alle <Dateiart> aus <Ordner> automatisch". Richtet IMMER zuerst einen Dry-Run ein und schaltet erst nach ausdrücklichem Nutzer-Go scharf; Löschen bleibt grundsätzlich im _trash-Modus.
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Teststrategie-Berater für Softwareprojekte — wählt die richtigen Teststufen (Unit/Integration/System/Abnahme), Testarten (funktional, nicht-funktional, änderungsbezogen) und Testentwurfsverfahren (Äquivalenzklassen, Grenzwerte, Entscheidungstabellen, explorativ) für die jeweilige Situation und SDLC-/CI-Phase, inkl. Testpyramide, CI/CD-Gates, Shift-Left und Best Practices. Nutze diesen Skill IMMER, wenn Tests geschrieben, geplant, priorisiert oder bewertet werden sollen — bei "schreibe Tests", "Teststrategie", "Testplan", "Testkonzept", "was/wie soll ich testen", "welche Tests fehlen", "Testabdeckung verbessern", "QA aufsetzen", Fragen zu Regression/Smoke/Sanity/Last/Stress/Security-Tests oder beim Einrichten einer Test-Pipeline — auch wenn "Test" nur beiläufig fällt. Abgrenzung — für die TDD-Schleife selbst superpowers:test-driven-development, für Bug-Diagnose bugfix-protocol, für systematische Bug-Suche bugsweep nutzen.
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