「engine」の検索結果

Recover deleted files from disk images and storage media using PhotoRec's file signature-based carving engine regardless of file system damage.

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。

Maps observed adversary behaviors, security alerts, and detection rules to MITRE ATT&CK techniques and sub-techniques to quantify detection coverage and guide control prioritization. Use when building an ATT&CK-based coverage heatmap, tagging SIEM alerts with technique IDs, aligning security controls to adversary playbooks, or reporting threat exposure to executives. Activates for requests involving ATT&CK Navigator, Sigma rules, MITRE D3FEND, or coverage gap 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。

Use when a feature launch needs experiment design, test sequencing, rollout guardrails, and measurement logic before exposure to users.

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。

Use before writing PlayCanvas behaviour from scratch, to reuse the scripts and helpers the installed Engine already ships.

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。

Use when creating or restructuring a PlayCanvas app with the Engine API, @playcanvas/react, or @playcanvas/web-components, covering bootstrap, input, resize, physics, update loop, UI, and lifecycle.

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。

Use when reading state from a running PlayCanvas app, to reach its live Application through the Engine devtools hook without changing app code.

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。

Use when you need to check whether an organisation/domain has been claimed by a ransomware group, profile a specific ransomware group (TTPs, leak-site infra, IOCs, YARA), or aggregate ransomware victim claims by country/sector/timeframe. Backed by ransomware.live's leak-site scrapes — 27k+ victims across 330+ groups. Commonly invoked by /domain-investigation, /ransomware-ecosystem, /threat-actor-profiling, and detection-engineering workflows. Reads $RANSOMWARE_LIVE.

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。

Go software engineering skill for designing, implementing, debugging, testing, reviewing, and refactoring Go applications, CLIs, APIs, services, concurrency code, modules, and tooling. Use for .go files, go.mod/go.sum, goroutines/channels, interfaces, error handling, performance profiling, race fixes, and idiomatic Go architecture.

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。

Prompt engineering and task-specification skill for improving prompts, agent instructions, system messages, evaluation prompts, coding-agent tasks, multi-step workflows, and LLM output reliability. Use when rewriting vague prompts, adding constraints, reducing ambiguity, improving safety, creating reusable prompt templates, or converting goals into actionable agent instructions.

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。

Assembly programming and low-level debugging skill for reading, writing, explaining, optimizing, and reviewing assembly across x86, x86-64, ARM, AArch64, RISC-V, calling conventions, ABI boundaries, inline assembly, disassembly, stack frames, registers, and binary-level behavior. Use for .s/.asm files, compiler output, reverse-engineering snippets, low-level performance, and crash 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。

Security Operations Center skill for alert triage, detection engineering, incident response, log analysis, threat hunting, SIEM queries, EDR investigation, timeline building, IOC handling, escalation notes, containment recommendations, and analyst-ready reporting. Use for blue-team operations, suspicious event analysis, and defensive cybersecurity workflows.

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。

Python engineering skill for implementing, debugging, testing, packaging, typing, reviewing, and refactoring Python applications, scripts, APIs, automation, data processing, CLIs, and libraries. Use for .py files, pyproject.toml, requirements files, pytest, async Python, type hints, packaging, dependency management, and Python performance or reliability work.

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。

Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.

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。

Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).

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。

Use this skill whenever the user asks for an HTML-first visual design deliverable or design judgment: interactive prototype, slide deck, motion demo, infographic, dashboard, landing page, whitepaper, changelog, business card, social cover, brand system, design critique, multi-variant exploration, or export to MP4, GIF, PPTX, PDF, or SVG. It is optimized to make AI agents do the routing, template selection, verification, and export prep so humans spend less time prompt-engineering. Do not use for production web apps, SEO sites, backend systems, or pure copy 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。

Agent-native design engine that makes AI do more useful work: route the prompt, fork a template, weave IFQ ambient craft, verify the artifact, and only install export tooling when requested. One prompt -> shippable HTML, with optional MP4 / GIF / PPTX / PDF / SVG. Triggers include prototype, hi-fi mockup, slide deck, motion demo, infographic, dashboard, whitepaper, changelog, business card, social cover, brand from scratch, design critique, mp4/gif export, 60fps, keynote, PPTX, A-vs-B benchmark. Do not use for production web apps, SEO-critical sites, backend systems, or pure copy 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。

MATLAB R2026a agentic workflow router. Use this whenever the user asks for MATLAB, Simulink, .m/.mlx/.slx work, toolbox-driven engineering, paper reproduction, simulation, code generation, data analysis, control, robotics, signal/image/AI workflows, or wants an end-to-end automated MATLAB task with validation. For Simulink tasks on this machine, default to a visible workflow: open MATLAB/Simulink windows first so the user can watch modeling, simulation, tuning, and plotting progress.

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。

MATLAB R2026a workflow for control systems, system identification, robust control, MPC, Simulink Control Design, parameter tuning, constrained optimization, and numerical validation. Use whenever the user asks for controllers, transfer functions, state-space models, tuning, identification, optimal control, or solver-based engineering.

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 multi-agent code review. Simulates a team of Principal Engineers reviewing code from different perspectives. Use when asked to review code, check a PR, analyze changes, or perform code 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。

"Apply mechanism design (reverse game theory) to engineer incentive-compatible rules for allocation problems. Use this skill when the user needs to design auctions, voting systems, or matching markets, or when evaluating whether a proposed mechanism satisfies incentive compatibility and individual rationality constraints.".

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。

Elite UX/UI & Advanced GSAP Motion Engineer. Enforces Python-driven true randomization for layout variance, strict AIDA page structure, wide editorial typography (bans 6-line wraps), gapless bento grids, strict GSAP ScrollTriggers (pinning, stacking, scrubbing), inline micro-images, and massive section spacing. Use when building motion-rich frontend pages with stricter GPT/Codex design enforcement.

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 and refine web UI—component structure, responsive layout, design tokens, state, and accessibility. Use for feature UI work beyond WCAG checks alone.

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。

Simplify working code while preserving behavior—remove dead paths, flatten nesting, clarify names, reduce duplication. Use after features work but code feels over-engineered.

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。

"Implement TF-IDF scoring to measure term importance relative to a document corpus. Use this skill when the user needs to rank documents by keyword relevance, extract important terms from text, or build a basic search relevance engine — even if they say 'find relevant documents', 'keyword extraction', or 'term importance'.".

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。