3,808 件 ・ 関連度順
Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD). Decades of experience writing reliable, optimized, and maintainable embedded code with deep expertise in memory barriers, DMA/cache coherency, interrupt-driven I/O, and peripheral drivers.
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。
Master binary analysis patterns including disassembly, decompilation, control flow analysis, and code pattern recognition. Use when analyzing executables, understanding compiled code, or performing static analysis on binaries.
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。
Für Rechtsabteilung: Change-Control-Klauseln im Konzernvertrag: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt. Fachgebiet: AGB-Recht-Prüfer. Route: rechtsabteilung-change-vertragsstrafe.
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。
Qualify a check before it is allowed to clear anything — prove it can detect the failure it is meant to catch. Seeds known defects into a copy of a real artifact plus a clean control, runs the checker, and reports recall and false-positive rate into a qualification ledger. Use when the user says "does this check work", "qualify the gate", "test my reviewer", "seed defects", "vaccinate", "qualify the checks", "can I trust this review", "does it pass for the right reason", or before relying on any automated check or referee simulation for a decision that matters. NOT a code fixer and NOT a reviewer itself — it grades the grader.
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。
Stress-test a finding against the choices you did not make. Enumerates the discrete forks a competent analyst could have taken (measure definition, sample filter, control set, clustering level, weighting, functional form), runs the specification grid, and reports the distribution rather than a point estimate — then attacks the identifying assumption with named, computable sensitivity statistics. Use when the user says "is this robust", "challenge this result", "specification curve", "multiverse", "how sensitive is this", "what if I'd used a different measure", "stress-test my estimate", or before a result becomes a headline claim. NOT a reviewer of prose or code — it challenges the CLAIM.
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。
Under genuine uncertainty with no reliable forecast, inventory means, cap downside at affordable loss, act for commitments, and let goals emerge from controllable moves.
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。
For authorized security review of code, auth, or APIs you control, model the attacker, map the attack surface, and report only findings with a reproducible exploit path and verified mitigation.
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。
When a real test is too rare, large, or irreversible, run a controlled counterfactual: isolate one variable, fix conditions, trace the mechanistic chain, and bound what the result implies.
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 Ian Xiaohei-style HTML/SVG motion illustrations for Chinese articles, scripts, storyboard scenes, workflow explanations, concept metaphors, and short video visual aids. Use when the user asks for 小黑 SVG、漫画感 HTML、分层 SVG 动效、把小黑生图做成 HTML/SVG、可编辑矢量动效、口播流程动画、手绘漫画动效、正文配图动画, or wants a Xiaohei illustration style adapted into controllable HTML/SVG/GSAP output instead of raster image generation.
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。
Extract anonymized frame-by-frame body and hand trajectories from an authorized reference video, with skeleton previews, confidence evidence, and machine-readable keypoints. Use when the user asks to 提取博主动作, 提取人体动作轨迹, 做姿态参考, 生成骨架视频, or prepare motion control data for an avatar; do not route graphic-animation replication here.
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。
提取微信公众号文章全文。Use when the user provides a mp.weixin.qq.com URL and asks for 提取文章, 抓取公众号, 读一下这篇, or when another skill (ra-洗稿, ra-选题, ra-video-wash-pipeline) needs to read a WeChat article before processing. Uses MicroMessenger UA spoofing to bypass WeChat's first-layer access control. Stdlib only, no API key required.
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 and control VFX in Unreal Engine 5 with Niagara: systems and emitters, modules and the spawn/update stages, exposed User parameters, and spawning or driving effects from Blueprints or C++. Use when building particle effects, NS_/NE_ assets, spawning a Niagara system at runtime, setting User parameters, or when the user mentions Niagara, VFX, or a particle system in Unreal.
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。
Wire player input in Unity 6.3 LTS with the Input System package: Input Actions, action maps, the PlayerInput component, and reading values via callbacks or polling. Use when the project has a .inputactions asset or com.unity.inputsystem, or when the user mentions the Unity Input System, InputAction, action maps, PlayerInput, control schemes, or rebinding.
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 Unreal Engine 5 C++ gameplay code: the UCLASS/UPROPERTY/UFUNCTION reflection macros, the Gameplay Framework (GameMode, Pawn, Character, PlayerController, Actor components), and the module Build.cs. Use when writing or debugging UE C++, deriving from AActor/ACharacter/ AGameModeBase, exposing properties to the editor or Blueprints, or when the user mentions Unreal C++, UCLASS, GENERATED_BODY, GameMode, ACharacter, or .Build.cs.
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 Phaser 4 Arcade Physics: enable the world, give sprites bodies, set velocity/acceleration/gravity, and resolve collisions with colliders, overlaps, groups, and world bounds. Use when a Phaser game needs movement or collisions — when the user mentions Arcade Physics, this.physics, setVelocity, collider, overlap, gravity, onFloor, or a platformer/top-down controller. For game config, scenes, and the loader use phaser-core.
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 a 2D platformer: run/jump control with coyote time, jump buffering, and variable jump height, plus tiled levels and hazards. Use for a platformer or Mario/Celeste-like, or tuning jump feel.
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 respawn-safe Roblox character systems around Players, CharacterAdded/CharacterRemoving, Humanoid, HumanoidRootPart, Animator, R6/R15 rigs, movement, animations and markers, death, tools, accessories, ownership, and custom characters. Use when character scripts break after respawn, cache stale Humanoids, control movement or velocity, load AnimationTracks, handle death, equip Tools, modify avatars, or support custom player rigs.
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 build game UI/UX — HUDs, menus, and overlays — that survive every screen: anchor- based responsive layout, resolution/aspect scaling and safe areas, keyboard/gamepad focus navigation, a screen/menu state stack, and event-driven (not polled) HUD updates. Engine- neutral patterns that pair with the detected engine's UI skill. Use when the user mentions HUD, health bar, main menu, pause menu, settings screen, UI layout, anchors, UI scaling, aspect ratio, safe area, controller/keyboard menu navigation, or wiring UI to game state.
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 2D kinematic character movement in Godot 4.7 with CharacterBody2D and move_and_slide(): platformer run/jump with gravity, top-down 8-direction motion, slope handling, and reading collisions. Use when coding a 2D player or enemy controller, a platformer or top-down character, or fixing move_and_slide()/ is_on_floor() behavior in a .tscn with a CharacterBody2D.
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 a first-person shooter: move+mouse-look controller, hitscan or projectile shooting, weapons, health, and enemy AI. Use for an FPS, or tuning aim feel, time-to-kill, recoil, or spread.
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。
Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.
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。
Interactive guided deployment flow for Azure OpenAI models with full customization control. Step-by-step selection of model version, SKU (GlobalStandard/Standard/ProvisionedManaged), capacity, RAI policy (content filter), and advanced options (dynamic quota, priority processing, spillover). USE FOR: custom deployment, customize model deployment, choose version, select SKU, set capacity, configure content filter, RAI policy, deployment options, detailed deployment, advanced deployment, PTU deployment, provisioned throughput. DO NOT USE FOR: quick deployment to optimal region (use preset).
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。
Generate natural, controlled prompt variants from a target-blind design brief and prompt architecture while preserving approved jobs, acts, journeys, constraints, roles, locales, proximity bands, and evidence language. Use after architecture design and before contamination or semantic QA.
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。
Select QA-approved canonical intent cells into a versioned AI-visibility tracking panel with partitions, variants, lanes, surfaces, locales, repetitions, separate exposure and priority weights, randomization, uncertainty, refresh rules, and campaign controls. Use after prompt QA or when revising an existing panel.
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。