Installs into .claude/skills of the current project.
Are you the author of Data Evaluation?
Add the live security badge to your README. It updates with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-data-evaluation)
---
name: data-evaluation
description: "Use OpenCDA's dumped YAML vehicle records for offline trajectory
augmentation, evaluation-output interpretation, plotting, and non-destructive
debugging."
disable-model-invocation: true
metadata:
disco-role: operating
license: NOASSERTION
---
# Data evaluation
Route offline work on OpenCDA data dumps, trajectory labels, evaluation outputs,
and debug plots here. This sub-skill is applicable when the input is a directory
of frame YAML files; it does not start a simulator or alter the source tree.
- Read [data-formats.md](references/data-formats.md) before interpreting vehicle
records, trajectory tuples, or observation/prediction horizons.
- Read [evaluation-and-plotting.md](references/evaluation-and-plotting.md) for
the evaluation lifecycle and saved debug artifacts.
- Read [troubleshooting.md](references/troubleshooting.md) when keys, horizons,
output paths, or plotting backends fail.
- For safe augmentation, run
[`scripts/generate_prediction_yaml.py`](scripts/generate_prediction_yaml.py)
with explicit `--input-root` and `--output-root`. It writes YAML only to a
separate output tree by default; use `--in-place` only when source mutation is
explicitly approved.
## Boundaries and external limits
This skill covers deterministic, offline post-processing and inspection. It
requires Python with PyYAML for the bundled helper and optionally matplotlib
for plots. `EvaluationManager` also imports CARLA and consumes live/in-memory
vehicle-manager state; a CARLA 0.9.12 client import was checked, but no CARLA
server was verified. SUMO, ScenarioRunner, torch, and YOLOv5 runtimes are not
part of the verified environment. Do not infer a successful simulator,
co-simulation, detector, or model evaluation from an offline YAML check.