649 件 ・ 関連度順
概要と使いどころ
当用户希望使用 msOpProf（`msprof op` / `msprof op simulator`）对昇腾 AI 算子做上板或仿真性能调优、解释 `aic-metrics`/`trace.json`/`visualize_data.bin`、选择 device vs simulator 路径、排查 `--soc-version`/`--export`/`signal 6`/`Bad address`/热点图或流水图相关问题，或要求生成固定分析报告模板（算子基本信息 / 关键数据 TOP5 / 核心瓶颈 TOP5 / 优化建议 TOP5）时，使用本技能。它负责先判定模式、输入形态与芯片/能力边界，再给出正确命令、结果解读、固定报告输出与高频踩坑规避；不要把经验案例当成通用规则。
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。
Analyze Ascend NPU schedule, operator dispatch, operator launch, and Host Bound profiling issues in Ascend profiling data. Use when need to diagnose device Free time, framework/operator dispatch latency, launch latency, PYTORCH_API/CANN_API launch gaps, aclrtSynchronizeStream stalls, task queue behavior, CPU scheduling interference, GC/lock pauses, CPU affinity, or schedule-side optimization actions.
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。
Verify NowStack Mobile iOS/Expo changes in the Apple Simulator with `xcrun simctl`. Covers single or parallel Metro/device flows, deep-link navigation, preview routes, and OTP sign-in. Use for `ns ios verification`, "test on simulator", or changed `mobile-app/**`; never use computer-use.
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 to migrate legacy Android camera implementations (Camera1 or raw Camera2 APIs) to CameraX. CameraX is a lifecycle-aware Jetpack library built on top of Camera2 that resolves camera rotation issues and handles device dependencies.
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。
Analyzes Android apps to identify key user workflows for AppFunctions such as creating a note, playing media, or sending an automated or AI agent triggered message, voice commands, or system shortcuts, without needing to open the app UI. Generates Kotlin code to expose these workflows to the Android system, allowing agents to discover and execute them on-device. Also refines KDoc documentation to ensure AI agents correctly understand and use the provided functionality.
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。
Deploy AI models to edge devices. TRIGGERS - Use when user needs help with ai-edge-deployment 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。
Utilize Shodan, the search engine for Internet-connected devices, to discover exposed assets, vulnerable ports, default credentials, and specific infrastructure configurations using advanced search queries (dorks).
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。
Deep OAuth 2.0 / OpenID Connect security assessment. Covers the full attack surface: redirect_uri validation bypass (path traversal, open redirect chains, subdomain confusion, URL parsing tricks, parameter pollution, response mode switching), missing/broken state parameter CSRF, PKCE downgrade and absent-challenge attacks, implicit grant token leakage (Referer, browser history, XSS fragment theft), authorization code injection, scope escalation, client confusion attacks, mutable-claims account takeover (iss+sub confusion, email-keyed identity merging), pre-account takeover via unverified registration, OpenID Connect dynamic client registration SSRF (logo_uri, jwks_uri, sector_identifier_uri, request_uri), nonce replay, ID token validation failures, Device Code phishing flow, mobile custom URI scheme hijacking, refresh token persistence, token introspection enumeration, consent screen clickjacking, host header injection, and cross-IdP mix-up attacks. Uses KOAuth, jwt_tool, nuclei oauth templates, and manual http(action="request", ...) payloads. Every technique includes actual request payloads and verification logic. Chains from /pentester or /api-security when OAuth endpoints are discovered. Chains into /web-exploit for open redirect, XSS, and SSRF chaining. Chains into /post-exploit when full account takeover is achieved. Chains into /credential-audit when access tokens or refresh tokens are recovered.
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。
Detects sensitive data stored insecurely on mobile devices (Android/iOS). Trigger on: SharedPreferences, NSUserDefaults, SQLite, Room DB, DataStore, Core Data, Keychain misconfiguration, external storage, backup exposure, plaintext files, unencrypted databases, adb backup, iCloud backup, NSFileProtection, EncryptedSharedPreferences, SQLCipher, allowBackup, FLAG_SECURE, keyboard cache, sensitive logs. Covers MASVS-STORAGE-1 (local storage) and MASVS-STORAGE-2 (exposure to unauthorized actors).
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。
Execute dynamic instrumentation utilizing Frida to inject custom JavaScript into running iOS applications (IPAs) on jailbroken devices. Hook native functions, bypass SSL Pinning, bypass Jailbreak Detection, and manipulate in-memory data at runtime.
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。
Identify and exploit default or weak credentials on web application login forms, admin panels, CMS backends (WordPress wp-admin, Joomla, Drupal), and embedded device management interfaces. Signals include framework fingerprinting (WhatWeb, Wappalyzer, Nikto), exposed admin paths from robots.txt/dirbusting, and weak password policy acceptance of "Password1" or "123456". Tools: Burp Suite Intruder, Hydra, Medusa, OWASP ZAP.
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。
Maestro mobile E2E testing - YAML flows, selectors, flow control, environment variables, JavaScript expressions, device interactions, Maestro Studio, Maestro Cloud CI, tags, test suites
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。
Detox E2E gray-box testing for React Native - matchers, actions, expectations, waitFor, device API, synchronization, mocking, artifacts, CI integration
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。
The measurement surface for ALL Pulp DSP and audio-pipeline work — read it BEFORE writing or gating DSP, not only when something already sounds wrong. Covers the C++ harness (signal generators, metrics, assertions, RenderScenario, contracts), the offline Audio Doctor (magnitude/frequency response, THD/THD+N, phase/group delay), and their Python sibling the Audio Quality Lab (tools/audio/quality-lab — null residual + alignment, LTAS log-spectral distance, spectral flux/centroid, HNR, Theil-Sen drift slope, Kaiser-sinc resampling, license-guarded corpus, regression-net ratchet). TRIGGER on AUTHORING work — "build/design an oscillator/filter/synth/effect", "add a DSP module", "what should the acceptance gate be", "how do I measure aliasing / anti-aliasing / alias floor", "null against a reference", "is this DSP correct", "choose a tolerance", "golden/regression corpus for audio", "measure drift or jitter", "A/B two renders" — AND on DEBUGGING work — "is there sound / no audio / I hear nothing", "does this filter/compressor/synth/delay produce the right signal", "prove the DSP / prove the contract", "measure the frequency response", "what's the THD / is it distorting", "what's the group delay / phase response / measured latency", "magnitude response curve", "render a test tone and assert", "audio regression", "64-frame works but 128 is silent", "sample-rate change pitch-shifted it", "describe what's in this buffer", "audio doctor", "compare before/after a DSP refactor". Reach for this BEFORE hand-rolling any FFT, null test, alias measurement, pitch tracker, or golden-render script — most of it already exists in one of the two lanes. Test/tool layer over HeadlessHost — deterministic, no audio device, no speakers. Off the realtime thread entirely.
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。
iOS platform development for Pulp — iPhone/iPad AUv3 app extensions, iOS Simulator builds, UIKit window host, CoreAudio IO audio, touch & Apple Pencil input, XcodeBuildMCP automation. Covers configure, build, deploy to simulator/device, and the gotchas discovered during iOS bringup.
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。
Unity New Input System correctness patterns. Catches common mistakes with action reading (triggered vs IsPressed vs WasPressedThisFrame), action map switching, rebinding persistence, InputValue lifetime, PassThrough vs Value, local multiplayer device assignment, and control scheme auto-switching. PATTERN format: WHEN/WRONG/RIGHT/GOTCHA. Based on Unity 6.3 LTS.
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 designing, implementing, or reviewing responsive frontend layouts, mobile-first breakpoints, container queries, fluid grids, data-dense tables, touch targets, safe areas, orientation changes, viewport overflow, or cross-device UI behavior; Chinese triggers include responsive layouts, mobile-side adaptation, breakpoints, container queries, horizontal and vertical screens, touch targets.
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 Electrical Engineer working in power systems — sizing a service or feeder from NEC demand factors, running a short-circuit study and checking breaker interrupting ratings, computing arc-flash incident energy and assigning a PPE category, checking protective-device coordination (selectivity), or reviewing a single-line diagram before construction.
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 Embedded/Firmware Engineer — analyzing worst-case execution time for a hard real-time deadline, choosing static over dynamic memory allocation to avoid fragmentation on a long-uptime device, keeping an interrupt service routine minimal and deferring work to the main loop, synchronizing a variable shared between an ISR and main context to prevent a torn read, or verifying a hardware register interaction against the datasheet's exact timing rather than observed bench behavior.
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 Crematory Operator — running a cremation cycle safely, verifying chain-of-custody and identification before charging a retort, handling implanted-device or oversized-decedent hazards, or documenting and troubleshooting an incident during processing.
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。
Pin-to-net mapping auditor -- verifies that every IC pin in the schematic is connected to the correct net, matched against a pin map source of truth (CSV, datasheet table, or Python dict). Critical for BGA/QFN devices where swap errors are invisible to DRC/ERC.
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 backup strategies that survive real disasters: 3-2-1 rule, versioning, testing restores, and covering all devices. Use when setting up backups or auditing whether current backups actually 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。
The user's synced Google Health Connect data from their Android device: daily metrics (steps, distance, calories, heart rate, HRV, VO2max), sleep sessions (stages, quality, efficiency), and workouts.
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。