4,176 件 ・ 関連度順
概要と使いどころ
Nature-style engineering manuscript reviewer skill for testing devices, robots, platforms, systems, algorithms embodied in physical systems and engineering methods against requirements, validation, benchmarking, uncertainty, robustness and failure modes.
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。
Design AI-powered pricing engines. TRIGGERS - Use when user needs help with ai-pricing-engine related tasks.
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。
Design AI personalization engines for content. TRIGGERS - Use when user needs help with ai-personalization-engine related tasks.
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。
Run AI agent tasks on a Volcengine (火山引擎) cloud phone via the Mobile Use Agent OpenAPI. Use when the user asks to drive, automate, operate, or test an Android app on a cloud phone for enterprise use cases (e.g. reply to WeCom customer messages, add leads in a CRM, clock in on DingTalk, check invoicing stats, query inventory in a supply-chain app, ship e-commerce orders, approve OA requests) or personal ones (open 小红书 and search, place an order, check nearby places on a map), or to check status, fetch result, cancel, or list a Mobile Use run. Requires one-time setup to store Volcengine AK/SK locally; ProductId and PodId can be saved as a default device during setup, the user prompt is provided per run. Supports optional GPS injection (GpsInfo) with user consent (auto-asked only for location-related tasks).
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。
Executes authorized phishing simulation campaigns to assess an organization's susceptibility to email-based social engineering attacks. The tester designs realistic phishing scenarios, builds credential harvesting infrastructure, sends targeted phishing emails, and tracks open rates, click-through rates, and credential submission rates to measure human security awareness. Activates for requests involving phishing simulation, social engineering assessment, email security testing, or security awareness measurement.
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。
Decompile, analyze, and reverse engineer Android applications (APKs). Utilize tools like JADX, Apktool, and dex2jar to extract source code (Java/Kotlin), analyze manifest configurations (Intents, Activities), and identify hardcoded secrets or insecure API endpoints.
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 building GBA games with the BPCore Lua engine - entity, sprite and tilemap functions, SRAM save and load, link cable multiplayer protocol, camera and scrolling, or optimization patterns
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。
Reverse engineers malware written in less-common compiled languages (Nim, Crystal, V, Zig, D) by detecting language-specific runtime signatures, name-mangling, and runtime strings to orient analysis. Activates for requests to reverse Nim malware, identify the source language of an exotic binary, or analyze Crystal/V/Zig/D compiled samples.
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。
Uses Ghidra to disassemble and decompile a binary, navigate to key routines via imports and strings, annotate decompiled code, and run headless scripts to automate extraction of C2, crypto, and config. Activates for requests to reverse engineer with Ghidra, decompile a binary, or script Ghidra headless 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。
Reverse engineers binaries using radare2/rizin interactively, covering analysis initialization, navigation, disassembly and graph views, patching, and the visual mode workflow. Activates for requests to reverse a binary with radare2 or rizin, learn r2 commands, or navigate and disassemble a sample in r2.
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。
Reverse engineers binaries with Binary Ninja using its analysis stack and Python API to enumerate functions, navigate IL levels (LLIL/MLIL/HLIL), and automate annotation and extraction. Activates for requests to reverse a binary with Binary Ninja, script the Binary Ninja API, or work with its intermediate languages.
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。
Reverse engineers ARM/AArch64 malware by identifying the architecture and instruction set state (ARM/Thumb), parsing ELF/Mach-O ARM headers, and orienting analysis around the ARM calling convention. Activates for requests to reverse ARM binaries, analyze AArch64 malware, or handle ARM/Thumb instruction-set decoding.
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。
Guided, section-by-section authoring of the master architecture document for the game. Reads all GDDs, the systems index, existing ADRs, and the engine reference library to produce a complete architecture blueprint before any code is written. Engine-version-aware: flags knowledge gaps and validates decisions against the pinned engine version.
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 task needs the judgment of a systems engineer/architect working at the whole-program level — decomposing requirements across hardware/software/network subsystems, writing or reviewing an interface control document (ICD), making a build-vs-buy tradeoff for a subsystem, or tracing a verification failure back through the requirements baseline. Distinct from a software engineer (owns one service's code) or DevOps/SRE (owns operational reliability) — this role owns the technical baseline for a whole system-of-systems and is accountable when subsystems built by different teams or vendors don't fit together.
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 task needs the judgment of a Civil Engineer — sizing stormwater detention/drainage systems, checking foundation bearing capacity against a geotechnical report, verifying IBC/ASCE 7 code compliance for site civil work, reviewing construction RFIs against stamped drawings, or evaluating value-engineering changes for safety-margin impact.
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 task needs the judgment of a Civil Engineering Technician — running and interpreting a concrete field acceptance test (slump, air content, cylinder breaks against ACI 318 criteria), verifying soil compaction against a Proctor density curve, reconciling a concrete or rebar quantity takeoff against a pay application, or documenting a field condition that deviates from the approved plans for the engineer of record.
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 task needs the judgment of an Automotive Engineer — computing weight transfer and tire friction-circle limits for a braking-while-cornering maneuver to set brake-force distribution, sizing a powertrain and gear ratio against a 0-60 mph acceleration target while checking traction versus power limits, sizing a crumple zone's crush distance against FMVSS 208 occupant-deceleration limits, or checking a powertrain-mount or driveline natural frequency against engine firing-order excitation for NVH isolation. Distinct from an automotive-service-technician (diagnoses and repairs a vehicle already designed) — this role owns the system-level design decisions (structure, powertrain sizing, suspension geometry, restraint/crash structure, NVH) that produce the vehicle the technician later services.
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 the user mentions tosutil, TOS object storage, bucket/object operations, batch upload or download, object metadata, TOS connectivity, or errors such as 403/network/argument failures. 围绕火山引擎对象存储 tosutil 生成与校验命令、规划桶/对象操作并诊断错误；当用户提到 tosutil、TOS 桶对象管理、批量上传下载或相关排障时调用。
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。
Generates structured engineering specs (backend or frontend) from feature descriptions, designs, or ticket references. Triggers on "spec", "story", "ticket", "engineering spec", "write a story for", "write a spec for", "create a ticket for".
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 interactive "living workflow" flowcharts in the visual style of https://statuesque-starship-49757d.netlify.app/revenue-engine - vanilla HTML/CSS/JS files with a horizontal step bar, a vertical trunk that grows per step, tool-to-tool columns with animated payload pills between brand-marked tool nodes, alternating left/right step descriptions, and per-step outputs. Use whenever the user says "build a flowchart", "interactive flowchart", "living workflow", "revenue engine flowchart", "demand gen flowchart", "GTM workflow diagram", "process diagram with animations", "Nebor-style flowchart", or asks to recreate the workflow visual from the Nebor site. Always asks which flowchart to build (Revenue Engine / Demand Gen / CRM & RevOps / Custom) and waits for explicit approval of the step + tool + edge table before generating any files.
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。
Design and implement features from raw data for machine learning models. Use when the user says "engineer features", "feature engineering for X", "create features from this dataset", "transform these variables", "encode categoricals", "handle skew", "create interaction features", "lag features", "extract features from text or dates", "improve model performance with better features", or wants to move from raw columns to model-ready inputs.
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。
Universal prompt engineering techniques for any LLM. Use when crafting, optimizing, or reviewing prompts for AI models. Triggers on requests like "improve this prompt", "write a system prompt", "optimize my instructions", "help me prompt engineer", "audit this prompt", "review my prompt", or when building agentic systems that need structured prompts.
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。
Understand what SKMTC is, how its engine works, and the architectural invariants — for agents building or extending infrastructure *around* SKMTC rather than authoring generators or running the CLI. Covers the three-phase pipeline, the host/Worker boundary, cross-generator coordination, the manifest, the attribution / gen-maps (provenance) subsystem, the package graph, the dependency substrate, and the design decisions that make SKMTC behave unlike a typical codegen tool. Use this skill when the user asks "what is SKMTC", "how does the SKMTC engine work", "explain the SKMTC architecture", or is building platform infrastructure around SKMTC — a hosted generate API, a schema or generator registry, tracing or provenance tooling, a web app or SaaS that wraps the engine, or platform-level CI integration. This skill is the system mental model. It does NOT cover authoring generators (→ skmtc-generator), running CLI commands (→ skmtc-cli), or diagnosing broken runs (→ skmtc-debug).
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。
Prevents overengineering when designing, implementing, refactoring, or reviewing software. Use when the user asks to implement a feature, add an abstraction, refactor code, review a design, simplify existing code, or make an architectural decision. Also triggers when the user asks if code is too complex, whether to abstract something, or how to structure something. Do not use for deployment, infrastructure configuration, or debugging runtime errors unrelated to code structure.
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。