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cccskills

데이터·AI 스킬

데이터 분석, 머신러닝, LLM 앱, 프롬프트 설계 (9천건)

가격이나 정렬 순서로 필터

Use when writing ANY async code, actors, or threads in an Apple-platform app, or seeing ANY concurrency error. Covers Swift 6 concurrency, @MainActor, Sendable, data races, async/await patterns.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

CharlesWiltgen/Axiom1.2천2026년 10월 21일 업데이트

Fetch WeatherKit current, minute, hourly, and daily forecasts; weather alerts; iOS 18+ changes, historical comparisons, summaries, and statistics; and required Apple Weather attribution. Use when integrating weather data, showing forecasts or alerts, caching WeatherKit responses, displaying attribution, or reviewing WeatherKit query limits in iOS apps.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

sensorkit

무료

Access research-grade sensor data using SensorKit for approved studies. Use when an app needs SensorKit entitlement setup, Research Sensor & Usage Data authorization, ambient light, recorded motion, device usage, keyboard metrics, visits, speech, face, wrist temperature, ECG, PPG, acoustic settings, or sleep-session data. Route ordinary motion to CoreMotion and health records/workouts to HealthKit.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

Implement computer vision features including text recognition (OCR), face detection, barcode scanning, image segmentation, object tracking, and document scanning in iOS apps. Covers both the modern Swift-native Vision API (iOS 18+) and legacy VNRequest patterns, VisionKit DataScannerViewController for live camera scanning, and CoreMLRequest/VNCoreMLRequest for custom model inference. Use when adding OCR, barcode scanning, face detection, or custom Core ML model inference with Vision.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

Build private, on-device AI features on iPhone, iPad, and Mac with Foundation Models, Core ML, MLX Swift, or llama.cpp. Use when choosing an Apple-local model runtime, building an Apple Intelligence chatbot or tool-calling feature, running an LLM on Apple Silicon, converting or compressing a Python model for Core ML, or comparing on-device inference backends. For Swift Core ML loading and prediction code, use the coreml skill.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

cryptokit

무료

Use Apple CryptoKit for Swift cryptographic primitives. Use when hashing with SHA-2 or SHA-3, generating HMACs, encrypting with AES-GCM or ChaChaPoly, signing with P256/P384/P521/Curve25519 or ML-DSA keys, performing ECDH, HPKE, ML-KEM, or X-Wing key exchange, using Secure Enclave CryptoKit keys, or migrating CommonCrypto code to CryptoKit.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

Tokenize, tag, and analyze natural language text using Apple's NaturalLanguage framework and translate between languages with the Translation framework. Use when adding language identification, sentiment analysis, named entity recognition, part-of-speech tagging, text embeddings, or in-app translation to iOS/macOS/visionOS apps.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

pdfkit

무료

Display and manipulate PDF documents using PDFKit. Use when embedding PDFView to show PDF files, creating or modifying PDFDocument instances, adding annotations (highlights, notes, signature widgets), extracting text with PDFSelection, navigating pages, generating thumbnails, filling PDF forms, or wrapping PDFView in SwiftUI.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

Access Core Motion accelerometer, gyroscope, magnetometer, device-motion, pedometer, activity-recognition, altitude, headphone motion, batched high-frequency workout motion, and water-submersion/depth data. Use when reading device sensors, counting steps, detecting walking/running/driving/cycling, tracking altitude, building motion interactions, handling AirPods head tracking, or implementing watchOS dive/depth features.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

core-data

무료

Build, review, or improve Core Data persistence in apps that have not adopted SwiftData. Use when working with NSManagedObject subclasses, NSFetchedResultsController for list-driven UI, NSBatchInsertRequest / NSBatchDeleteRequest / NSBatchUpdateRequest for bulk operations, NSPersistentHistoryChangeRequest for persistent history tracking and multi-target sync, NSStagedMigrationManager for staged schema migrations (iOS 17+), NSCompositeAttributeDescription for composite attributes (iOS 17+), or when integrating Core Data threading with Swift Concurrency. For Core Data + SwiftData coexistence or migration, see the swiftdata skill instead.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

Read, create, update, and pick contacts using the Contacts and ContactsUI frameworks. Use when fetching contact data, saving new contacts, wrapping CNContactPickerViewController in SwiftUI, handling contact permissions, or working with CNContactStore fetch and save requests.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

dpearson2699/swift-ios-skills1.2천2026년 8월 1일 업데이트

Run explicitly requested Autoprompt work with task routing, owned assignments, independent checks, and bounded recovery.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Spielewoy/autoprompt-skill1.2천2026년 10월 4일 업데이트

Run explicitly requested Autoprompt v2 work through the private controller. Ordinary coding and review requests do not activate this skill.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Spielewoy/autoprompt-skill1.2천2026년 10월 4일 업데이트

TikTok Shop analytics and performance tracking. Video metrics, live selling data, affiliate performance, advertising analytics, and business intelligence. Use when the user asks about TikTok Shop analytics, performance tracking, metrics analysis, or data-driven optimization.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nexscope-ai/eCommerce-Skills1.2천2026년 8월 26일 업데이트

Platform migration to Shopify — from WooCommerce, Magento, BigCommerce, data transfer, URL redirects

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nexscope-ai/eCommerce-Skills1.2천2026년 8월 26일 업데이트

Shop analytics — traffic sources, conversion rates, search terms, top listings performance

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

nexscope-ai/eCommerce-Skills1.2천2026년 8월 26일 업데이트

Deep competitive intelligence for any market. Analyzes competitors' products, pricing, customer sentiment, GTM strategy, and growth signals using real web data. Produces battle cards, pricing landscape, and feature matrix. Use when the user wants to understand their competitive landscape, analyze competitors, compare products in a market, or research who they're competing against. Triggers for "who are my competitors", "competitive analysis", "competitor research", "battle cards", "pricing comparison", "competitor pricing", "market players", "competitive intelligence", "competitive landscape", "who else is in this space", "competitive moat", or any request to profile, compare, or map competitors in a category. Works standalone — no prior startup-design session needed.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

ferdinandobons/startup-skill1.2천2026년 7월 1일 업데이트

Create a reusable SkillPack from a successful completed task. Use when the user wants to convert a one-off research, coding, analysis, or content workflow into a distributable local SkillPack with `skillpack.json`, local skills under `skills/`, starter prompts, start scripts, and an optional zip package.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

CreminiAI/skillpack1.2천2026년 9월 16일 업데이트

Set up and run wireless network simulations using the Wireless Network Toolbox. Use this skill when creating system-level simulations with wirelessNetworkSimulator, adding traffic sources (networkTrafficOnOff, networkTrafficFTP, networkTrafficVoIP, networkTrafficVideoConference), configuring node mobility, logging events or IQ samples, visualizing traffic, scheduling actions during simulation, running parametric sweeps, writing PCAP files with pcapWriter or technology-specific PCAP writers, registering event callbacks on wireless nodes, accessing event data fields, or combining multiple capture/visualization tools in a simulation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matlab/matlab-agentic-toolkit1.2천2026년 10월 14일 업데이트

Simulate Bluetooth system-level networks using the Bluetooth Toolbox. Use this skill for any Bluetooth topology: BLE ACL (Asynchronous Connection-Less) data connections, CIS (Connected Isochronous Stream) and LE Audio for stereo speakers or hearing aids, BLE GAP (Generic Access Profile) connection establishment with advertising and scanning, Classic BR/EDR piconets with ACL data and SCO (Synchronous Connection-Oriented) voice links, and BLE+BR/EDR coexistence with adaptive frequency hopping. Covers bluetoothLENode, bluetoothNode, bluetoothLEConnectionConfig, bluetoothLECISConfig, bluetoothLEGAPConfig, bluetoothConnectionConfig, configureConnection, kpi (), updateChannelList, and all Bluetooth statistics.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matlab/matlab-agentic-toolkit1.2천2026년 10월 14일 업데이트

Use this skill when conditioning, loading, preparing, or labeling signal data for analysis or ML training. Covers: cleaning a single signal (fill gaps, remove drift, deoutlier, denoise, resample/align a time base) BEFORE analysis; building a `signalDatastore` pipeline; creating a `labeledSignalSet` for Signal Labeler; deriving labels (filename, folder, in-file, ROI, time-frequency ROI); stratified train/val/test splits; framing long signals; parallel processing; and shaping datastore output for `trainnet`. Triggers include "clean up this signal", "remove drift / detrend", "fill gaps", "remove spikes / outliers", "denoise", "resample to a uniform rate", "align channels", "labels from filenames", "stratified split", "prepare for Signal Labeler", and function names like `fillgaps`, `fillmissing`, `detrend`, `filloutliers`, `smoothdata`, `resample`, `synchronize`, `signalDatastore`, `labeledSignalSet`, `filenames2labels`, `folders2labels`, `splitlabels`, `framesig`, `framelbl`, `createDatastores`.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matlab/matlab-agentic-toolkit1.2천2026년 10월 14일 업데이트

RF Toolbox and RF Blockset in MATLAB -- S-parameter I/O, network conversions (S/Z/Y/ABCD/T/H/G, mixed-mode), cascade/de-embedding, rfbudget analysis, circuit composition, matching networks, amplifier stability, mixer spurs, rational fitting, SI channels, baseband processing, Circuit Envelope simulation. Trigger: sparameters, Touchstone, .s2p, .s4p, rfplot, smithplot, rfparam, rfwrite, zparameters, yparameters, abcdparameters, s2sdd, cascadesparams, deembedsparams, rfbudget, noise figure, OIP3, IIP3, amplifier, modulator, nport, rffilter, attenuator, seriesRLC, shuntRLC, lcladder, txline, circuit, setports, clone, matchingnetwork, stabilityk, stabilitymu, powergain, gammams, gammaml, mixerIMT, OpenIF, rational, rationalfit, stepresp, txlineWRLGC, rf.Amplifier, rf.Mixer, rf.Filter, rf.Sparameter, rfsystem, RF Blockset.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matlab/matlab-agentic-toolkit1.2천2026년 10월 14일 업데이트

Extract features from 1D signals using signalTimeFeatureExtractor, signalFrequencyFeatureExtractor, and signalTimeFrequencyFeatureExtractor. Use when computing time-domain features (amplitude, energy, shape factors), frequency-domain features (spectral location, power, bandwidth, PSD), or time-frequency features (spectral shape, instantaneous, ridges, wavelet, EMD-derived) on a per-frame basis. Use when the user asks to "extract features", "compute spectral features", "build a feature table for a classifier", "get per-frame statistics", "run feature extraction on this signal", or describes a vibration / biosignal / radar / sensor signal needing features for downstream ML or analysis. Includes optional GPU acceleration via canUseGPU and gpuArray. Does not cover filter design, audio-specific feature extraction (use audioFeatureExtractor in Audio Toolbox instead), batch dataset orchestration, or 2D / image features.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matlab/matlab-agentic-toolkit1.2천2026년 10월 14일 업데이트

Analyzes sensor configurations and creates inertial fusion filters in MATLAB Navigation Toolbox. Manages filter selection (imufilter, ahrsfilter, complementaryFilter, insfilterMARG, insfilterAsync, insfilterNonholonomic, insfilterErrorState, insEKF, insCF), construction, tuning, and fusion loops. Use when fusing IMU/AHRS/INS/GPS+IMU data, estimating orientation or pose, or choosing a filter. Do NOT use for vision-only SLAM, Simulink fusion, or IMU simulation.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

matlab/matlab-agentic-toolkit1.2천2026년 10월 14일 업데이트