debug-grid-cell_skill

Overview

This skill is a debug tool that queries a specific cell in an observed voxel grid relative to the agent. It returns a concise summary and a structured data object describing the cell at the requested agent-relative coordinates. It is intended for testing and verifying coordinate systems, visibility, and block properties in environments that expose a voxel observation grid.

How this skill works

You call the skill with agent-relative coordinates (dx, dy, dz) and an optional radius to limit the observation area. The skill inspects the observed voxel grid at the requested location and returns a uniform response containing a human-readable value and a data dictionary. The data dictionary reports the coordinates, block identifier (or null), and boolean flags for solidity and support.

When to use it

• Verifying that agent-relative coordinate math maps to observed voxels correctly.
• Testing whether a particular cell is occupied or empty during environment debugging.
• Confirming block IDs and support properties for pathfinding or physics experiments.
• Quickly checking nearby cells without scanning the entire observation grid.
• Unit testing or integration tests that need deterministic voxel queries.

Best practices

• Provide agent-relative coordinates to avoid confusion with world or global frames.
• Use the default radius for single-cell checks; increase radius only when needed.
• Handle null block_id as an empty or unknown cell in downstream code.
• Treat solid and support as independent booleans; a cell can be solid but not provide support.
• Keep debug calls out of production planners; use them only in testing or diagnostics.

Example use cases

• Check the cell directly in front of the agent to validate collision detection.
• Inspect the block under the agent to confirm support before attempting to stand or jump.
• Validate coordinate transforms during agent rotations by querying symmetric offsets.
• Automated tests that assert expected block_id and solidity at specific relative positions.
• On-demand diagnostics when environment behavior diverges from expectations.