Results for “load-data-infile”

Ingests music into a LanceDB via ncmdump-rs and sf-cli, searching and downloading from Netease Cloud Music or Bilibili, decrypting local NCM files, and extracting metadata, lyrics, and cover art.

Wire ETL, ingestion, cron, edge-function, and queue jobs correctly. Use for "build a pipeline", "sync X into Y", "nightly aggregation", "cron double-counts", "dedupe", "backfill", "the numbers are wrong after a retry". Bakes in idempotency, atomic writes, data contracts, dead-letter, and observability.

Generate `.claude/PROJECT_PROFILE.md` — the project-specific facts that should be loaded into every session (deployment topology, host mapping, env file locations, verification commands). Run once per project after clone.

Load sharded datasets (npy, Parquet, HDF5, raw binary) into distributed cuPyNumeric arrays using manual partitioning and Legate task launches.

Implement file upload endpoints in ASP.NET Core minimal APIs (.NET 8+) with size limits, content validation, and streaming.

Diagnose and optimize slow-loading, high-memory, or low-FPS USD scenes using a structured workflow with profiling, validation, and mutation phases.

Merges CSV/TSV data with an InDesign template to generate personalized PDFs like certificates, badges, and catalogs.

Imported skill load from langchain

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`.

Continues deep iteration on an existing planning document: detects explicit file-loading intent, provides status summaries, and supports on-demand in-depth exploration.

Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs using pandas for behavioral analytics and statistical baselines.

Ad-Hoc Raw Upload to Databricks

Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset correction, crop, normalizeTimestamps, convertTimestamps. Also: compute actor tracks from lidar when no annotations exist, attach camera/lidar mounting + intrinsics, export to MAT/workspace/timetable/script. Use for raw driving dataset files (KITTI, nuScenes, Waymo, Pandaset, ROS/ROS2 bags, .mat, .csv, .mp4) or driving/vehicle/sensor logs that need wrapping. drivingLogAnalyzer (DLA) is OPT-IN ONLY — invoke only on explicit user request ('DLA', 'open in DLA', 'inspect/explore/analyze the recording') or reported sensor problem (sync drift, timestamp mismatch, overlay misalignment). NEVER auto-launch DLA after wrapping (Rule 0). For 'build scenario / export to RoadRunner / drivingScenario / OpenSCENARIO / Unreal / simulate', hand off to matlab-use-scenario-builder.

Load 3D models, textures, and HDR environments in Three.js with GLTF, OBJ, FBX, STL, PLY, and Draco/KTX2 compression support.

Feature Intake

Imported skill loading from langchain

Store and retrieve files on IPFS (InterPlanetary File System). Use when a user asks to store files in a decentralized way, pin content on IPFS, upload NFT metadata, or use content-addressed storage.

Ingests case studies, past proposals, and boilerplate from library/inbox into structured indexes. Use when the user requests to 'index proposal library', 're-index case studies', 'ingest inbox docs', or 'validate library'.

Creates and maintains persistent markdown planning files that survive session resets by hooking into Claude Code's lifecycle.

Expert at handling file uploads and cloud storage. Covers S3, Cloudflare R2, presigned URLs, multipart uploads, and image optimization. Knows how to handle large files without blocking. Use when "file upload, S3, R2, presigned URL, multipart, image upload, cloud storage, file-upload, s3, r2, storage, presigned, images" mentioned.

Manage Uploadcare files through natural language: list, store, inspect, download, and organize file groups.

Three.js asset loading - GLTF, textures, images, models, async patterns. Use when loading 3D models, textures, HDR environments, or managing loading progress.

AIDE file integrity monitoring reference. Database initialization, integrity checks, update workflow, aide.conf configuration, selection rules, report parsing, and production deployment with CIS benchmark compliance.

Build ETL pipelines with data ingestion, cleaning, and validation steps. Use when ingesting sources, transforming formats, validating data, or scheduling loads.

Creates or updates Salesforce metadata components at runtime from Apex using the Metadata namespace, including custom fields, objects, picklist values, and labels, with asynchronous deployment and callback handling.

Loads one or more predefined role files to focus work on a specific task, activated by commands like "role [name]".

Import HD Map or OpenDRIVE files into a RoadRunner scene using MATLAB. Use when loading driving scenes in RoadRunner or RoadRunner Scene Builder, importing RRHD, OpenDRIVE, or other RoadRunner-supported formats for simulation, or verifying Lanelet2-to-RRHD conversion results visually. Requires rrApp handle from roadrunner-core.

Expert at handling file uploads and cloud storage. Covers S3, Cloudflare R2, presigned URLs, multipart uploads, and image optimization. Knows how to handle large files without blocking. Use when: file upload, S3, R2, presigned URL, multipart.

Use to push call recordings into Rulebase over the REST API when the phone system has no native connection, in reviewed batches with a dry-run plan, resume and audit log. Trigger for "upload calls to Rulebase", "import call recordings", "backfill our call history into Rulebase", "get XCally calls into Rulebase", "Rulebase isn't seeing our calls", or bulk-ingesting audio for QA evaluation.

HuggingFace hf CLI: search/download/upload models, datasets.

Configure AIDE for file integrity monitoring, including baseline creation, scheduled integrity checks, change detection, and alerting.

百度网盘(Baidu Drive)文件管理 — 上传、下载、转存、分享、搜索、移动、复制、重命名、创建文件夹。TRIGGER: 用户提及"百度网盘/bdpan/网盘/云盘/baidu drive/Baidu Drive"并涉及文件操作。DO NOT TRIGGER: 非文件存储操作，或使用其他云盘服务时。

Add a source file to the processing queue. Checks for duplicates, creates archive folder, moves source from inbox, creates extract task, and updates queue. Triggers on "/seed", "/seed [file]", "queue this for processing".

Break a trusted implementation plan (or other provided context) into independently-grabbable, atomic work items, written to a single work-items.md file. Use when the user wants to convert a plan into work items, create implementation tickets or tasks, divide a plan into work units, or break the plan down into grabbable pieces. Do not use when there is no implementation plan yet or the plan is not yet trusted — use plan-implementation to produce the plan or iterative-plan-review to harden it first. Does not sequence work into demoable delivery phases — use plan-a-phased-build for that. Does not write code — use tdd to implement a work item.

Uploads a file to Google Drive with automatic MIME type detection and optional parent folder or custom filename.