Driving Data Importer

by matlab

Driving Data Importer is an Automation skill for Claude Code, published by matlab in matlab-agentic-toolkit.

938 stars115 forkson matlab/matlab-agentic-toolkitAdded 2026/08/21+2% in starsRepository updated 2026/08/13

View source on GitHub Download repo ZIP

agent-skillsclaude-codecodex-pluginengineering-agentsgithub-copilotmatlabmatlab-mcp-server

Install in seconds

Install Driving Data Importer

Copy Driving Data Importer into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/matlab/matlab-agentic-toolkit/tree/main/skills-catalog/automotive/matlab-import-driving-data ~/.claude/skills/matlab-import-driving-data

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/matlab/matlab-agentic-toolkit.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills-catalog/automotive/matlab-import-driving-data/SKILL.md in matlab/matlab-agentic-toolkit
Installs to: ~/.claude/skills/matlab-import-driving-data
Collection: One of 25 skills cataloged from this repository
Category: Automation — 1523 skills

What Driving Data Importer does

Driving Data Importer loads raw driving sensor logs into scenariobuilder objects and runs preprocessing such as sync, crop, offset correction, and timestamp normalization. Use it when converting datasets like KITTI, nuScenes, Waymo, ROS bags, or CSV/MAT/video files for later scenario work.

Driving Data Importer is cataloged under Automation on DirSkills. Driving Data Importer comes from a repository tagged agent-skills, claude-code, codex-plugin, engineering-agents and github-copilot.

Documentation

README

Excerpt

Driving Data Importer

This skill loads raw driving sensor data into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and provides the CLI for every preprocessing step DLA exposes (sync, crop, offset, normalize, convert timestamps). It also covers the drivingLogAnalyzer (DLA) app as an opt-in inspection tool — see Rule 0 below; DLA is never a default step.

After wrapping is done, the canonical next move is matlab-use-scenario-builder (trajectory smoothing, scene/scenario generation, lane localization, RoadRunner / drivingScenario / OpenSCENARIO / OpenDRIVE / OpenCRG / Unreal export).

Rule 0 — DLA is opt-in only (HARD RULE, READ FIRST)

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Driving Data Importer

What else does matlab publish alongside Driving Data Importer?
Driving Data Importer is one of 25 skills that DirSkills catalogs from matlab/matlab-agentic-toolkit, the repository it ships in. Its siblings there include Aerospace Fundamentals, Build RoadRunner Scenario From OpenSCENARIO and Compute Aerospace Environment. Each one is a separate skill with its own page in this directory, installs the same way Driving Data Importer does, and is maintained by matlab in that same repository. The rest of the collection is listed on the matlab/matlab-agentic-toolkit page.
How does Driving Data Importer compare to other Automation skills?
Driving Data Importer ranks #876 by stars among the 1523 Automation skills in this catalog. The most-starred ones next to it are Autonomous Loops, Autonomous Agent Harness and Automation Audit Ops. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Driving Data Importer against them. Open each page to compare what they document and how they install.