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概要と使いどころ
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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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.
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。
Write and deploy Falco rules with the modern eBPF driver to detect container escape, namespace abuse, privileged mounts, and anomalous syscalls at runtime in Kubernetes and Docker.
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Implement a vulnerability aging dashboard and SLA tracking system to measure remediation performance against severity-based timelines and drive accountability.
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 and analyzes the Windows Amcache.hve registry hive to extract evidence of program execution, application installation, and driver loading for digital forensics investigations. Uses Eric Zimmerman's AmcacheParser and Timeline Explorer for artifact extraction, SHA-1 hash correlation with threat intel, and timeline reconstruction. Activates for requests involving Amcache forensics, program execution evidence, Windows artifact analysis, or application compatibility cache investigation.
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Use Sysinternals Autoruns to systematically identify and analyze malware persistence mechanisms across registry keys, scheduled tasks, services, drivers, and startup locations on Windows systems.
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 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.
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。
Drive the card's Review Hero loop by hand — trigger a review, address its comments, rerun until clean, then merge. Use in an external tool (Claude Code, Cursor) where Workhorse's automated loop isn't running.
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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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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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Google Workspace CLI for Gmail, Calendar, Drive, Contacts, Sheets, and Docs.
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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.
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。
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.
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, start, and drive the Nuxt Theme Builder in a real browser (Playwright) to verify a change end to end — editor interactions, iframe preview sync, persistence across reloads, source view. Use when asked to run/start/screenshot the app or to prove a UI or persistence change works beyond unit tests.
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。
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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Verify a tested web agent's real behavior from its recorded Pi or Codex session and selected screenshots before scoring. The judge prompt provides absolute artifact paths; use targeted queries to compare actual outputs, errors, and the final answer with the recorded behavior, then return only the verdict JSON. Only for ego-bench judging—never to drive a browser or rerun the agent.
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기능의 external behavior를 Cucumber 인수 테스트(주 검증층)로 구축 — .feature 실행으로 문서↔코드 드리프트를 구조적으로 차단, Four Layer(Steps→Protocol Driver→SUT), 태그 기반 가역 제외, 기존 JUnit 인수 테스트 이관. "인수 테스트 도입", "Gherkin을 실행 가능하게", "cucumber 셋업" 요청 시 사용. /cucumber-acceptance로 호출.
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。
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.
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。
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.
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 a new App Store Connect app record via browser automation. Use when there is no public API for app creation and you need an agent to drive the New App form.
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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.
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。
Determine whether an app is ready to submit, then drive the current App Store release flow with asc, including validation, staging, review submission, first-time availability, subscriptions, IAP, Game Center, and App Privacy checks.
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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.
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。