TF2 Transforms Skill
Expert skill for ROS tf2 coordinate frame management and transforms
npx skills add a5c-ai/babysitter --skill tf2-transforms --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# TF2 Transforms Skill ## Overview Expert skill for managing ROS tf2 coordinate frames, transform broadcasting, and debugging transform connectivity issues. ## Capabilities - Configure static transforms for robot links - Implement dynamic transform broadcasters - Set up tf2 listeners with time synchronization - Debug transform chains and connectivity - Configure transform lookup caching - Implement transform extrapolation - Set up multi-robot namespaced transforms - Configure map-odom-base_link chain - Implement sensor frame transforms - Debug TF_REPEATED_DATA and other issues ## Target Processes - robot-system-design.js - robot-calibration.js - sensor-fusion-framework.js - visual-slam-implementation.js ## Dependencies - tf2_ros - tf2_geometry_msgs - tf_transformations ## Usage Context This skill is invoked when processes require coordinate frame setup, transform debugging, or multi-robot TF configuration. ## Output Artifacts - Static transform launch files - Transform broadcaster nodes - TF tree configurations - Debug analysis reports - Namespaced TF setups - Time synchronization configs
- Overview
- Capabilities
- Target Processes
- Dependencies
- Usage Context
- Output Artifacts
What does the TF2 Transforms Skill skill do?
Expert skill for ROS tf2 coordinate frame management and transforms
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill tf2-transforms --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.