"Guides MASt3R-SLAM benchmark dataset manifests, evaluation command
Scanned 9/8/2026
Install to Claude Code
npx -y skills add VectorSpaceLab/AREX-Skill --skill evaluation --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Evaluation?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/vectorspacelab-evaluation-19498c99)More formats (shields.io, HTML) on the badges page.
---
name: evaluation
description: "Guides MASt3R-SLAM benchmark dataset manifests, evaluation command
planning, headless suite runs, output paths, and evo_ape metrics."
disable-model-invocation: true
metadata:
disco-role: operating
license: NOASSERTION
---
# evaluation
Use this sub-skill when the task is about TUM-RGBD, 7-Scenes, EuRoC, or ETH3D
benchmark workflows: dataset acquisition planning, sequence lists, headless
suite runs, `--no-calib` variants, trajectory output paths, or `evo_ape` metrics.
## Triggers
- "run MASt3R-SLAM evaluation"
- "download TUM/EuRoC/ETH3D/7-Scenes"
- "what sequences are in eval_tum.sh"
- "compute APE/evo metrics"
- "print the eval commands"
- "metric-only after a previous run"
- "where are logs for calibrated vs no-calib runs"
## Prerequisites
- Environment, CUDA backend, and checkpoints are owned by
[setup-and-backends](../setup-and-backends/SKILL.md).
- Single-sequence runtime command details are owned by
[run-slam](../run-slam/SKILL.md).
- Benchmark runs are long, GPU-heavy, and data-heavy. Print commands and ask for
approval before executing downloads or full-suite runs.
## First reads and scripts
- [references/evaluation-workflows.md](references/evaluation-workflows.md) for
suite command shapes and calibration variants.
- [references/dataset-layouts.md](references/dataset-layouts.md) for dataset
manifests and expected directory layouts.
- [references/metrics-and-outputs.md](references/metrics-and-outputs.md) for
log/trajectory/groundtruth and `evo_ape` path rules.
- [references/troubleshooting.md](references/troubleshooting.md) for missing
data/logs/metrics issues.
- [scripts/plan_evaluation.py](scripts/plan_evaluation.py) to reproduce the
upstream `eval_*.sh` command plan safely.
- [scripts/plan_downloads.py](scripts/plan_downloads.py) to print dataset
download manifests without performing network actions.
## Safe workflow
1. Print the download plan:
```bash
python sub-skills/evaluation/scripts/plan_downloads.py --suite tum --commands
```
2. Print the evaluation plan:
```bash
python sub-skills/evaluation/scripts/plan_evaluation.py --suite tum --no-calib
```
3. Verify checkpoints, datasets, and available runtime budget.
4. Execute only the approved subset, usually one sequence first.
5. Run metric-only mode when trajectories already exist instead of rerunning
SLAM.
## Important suite differences
- TUM, 7-Scenes, and EuRoC support both calibrated and no-calibration variants
in the upstream scripts.
- ETH3D uses the `eth3d.yaml` evaluation config and does not expose `--no-calib`
in the upstream eval script.
- All evaluation scripts run `main.py` in single-threaded, headless mode and
then call `evo_ape tum ... -as`.
## Boundary decisions
This sub-skill adapts the upstream shell scripts into print-first Python
planners. It should not auto-download archives or run multi-hour evaluations
unless the user explicitly approves that side effect.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!