Arize Evaluator
github/awesome-copilot
Handles LLM-as-judge evaluation workflows on Arize including creating/updating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and…
Use Torch Points3D Hydra training, evaluation, Trainer, checkpoints, forward inference, visualization, and experiment-output helpers.
Custom licenceAuto-check passed
Install Training Evaluation
$ npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill training-evaluation --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation .claude/skills/training-evaluation && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "training-evaluation" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation into .claude/skills/training-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "training-evaluation", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill training-evaluation --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation .agents/skills/training-evaluation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "training-evaluation" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation into .agents/skills/training-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "training-evaluation", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill training-evaluation --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation .cursor/skills/training-evaluation && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "training-evaluation" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation into .cursor/skills/training-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "training-evaluation", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/VectorSpaceLab/AREX-Skill.git --path skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill training-evaluation --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation .gemini/skills/training-evaluation && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "training-evaluation" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation into .gemini/skills/training-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "training-evaluation", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install VectorSpaceLab/AREX-Skill training-evaluationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation .github/skills/training-evaluation && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "training-evaluation" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation into .github/skills/training-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "training-evaluation", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill training-evaluation --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation .opencode/skills/training-evaluation && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "training-evaluation" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation into .opencode/skills/training-evaluation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "training-evaluation", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
training-evaluation- GitHub stars
- 330
- Token cost
- ~1.2k tokens
- SKILL.md length
- 410 words
- Files
- 9 (incl. scripts, references)
- Skills in repo
- 159
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Use Torch Points3D Hydra training, evaluation, Trainer, checkpoints, forward inference, visualization, and experiment-output helpers.
- SKILL.md covers Read First, Main Workflows, Boundary Rules and Safety Checklist
- Runs Python scripts from its folder; calls python
What it does
Training Evaluation is an agent skill from VectorSpaceLab/AREX-Skill. Use Torch Points3D Hydra training, evaluation, Trainer, checkpoints, forward inference, visualization, and experiment-output helpers.
Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `references/configuration-and-checkpoints.md`, `references/forward-inference.md` and `references/training-evaluation-workflows.md`).
The repository describes itself as: A Skill Library for Automated Machine Learning.
Example prompts
- “/training-evaluation”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit ac3fe1a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 4 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Training Evaluation loads about 1.2k tokens when it runs, and up to ~5.2k if it reads all its reference files. Until then it costs about 38 tokens; SKILL.md has 410 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 410 words (~1,195 tokens).
“Use this sub-skill when the user asks to compose Torch Points3D train.py or eval.py commands, debug Trainer, resume or evaluate checkpoints, inspect outputs// runs, configure W&B/TensorBoard/visualization, or run forward inference on unlabeled data from a trained checkpoint.”
- name
- training-evaluation
- disable-model-invocation
- true
- metadata.disco-role
- operating
- license
- NOASSERTION
Files
SKILL.md and 8 other files (scripts, references) in skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation of VectorSpaceLab/AREX-Skill.
- SKILL.md
- references/configuration-and-checkpoints.md
- references/forward-inference.md
- references/training-evaluation-workflows.md
- references/troubleshooting.md
- scripts/compose_config_smoke.py
- scripts/convert_checkpoint_omegaconf.py
- scripts/forward_preflight.py
- scripts/summarize_runs.py
Open the folder on GitHubat commit ac3fe1a
Compare with similar skills
Training Evaluation next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Training Evaluation this skillVectorSpaceLab/AREX-Skill | 330 | — | ~1.2k | Automated safety check: Pass | Custom licence | |
| Arize Evaluatorgithub/awesome-copilot | 40k | 1 repos | ~8.1k | Automated safety check: Notes | MIT | |
| Ray Train Distributed TrainingOrchestra-Research/AI-Research-SKILLs | 13k | 2 repos | ~2.7k | Automated safety check: Pass | MIT | |
| Ito Trainingaffaan-m/ECC | 276k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| LLM Evaluationdavila7/claude-code-templates | 32k | 12 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Train Poseruvnet/RuView | 97k | — | ~504 | Automated safety check: Pass | MIT |
Similar skills
- Official
Ray Train Distributed Training
Orchestra-Research/AI-Research-SKILLs
Scales PyTorch, TensorFlow and Hugging Face training from a single GPU to multi-node clusters with Ray Train, including Ray Tune sweeps and checkpoint recovery.
Ito Training
affaan-m/ECC
Inspect the availability of ML training on a completed Itô compute booking and, when the canonical backend becomes available, hand off an explicitly confirmed training manifest.
LLM Evaluation
davila7/claude-code-templates
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B testing.
Train Pose
ruvnet/RuView
Train/evaluate WiFi pose models honestly — camera-supervised (MediaPipe + CSI) and camera-free (WiFlow), always checked against the mean-pose baseline before any PCK is quoted.
Agent Evaluation
sickn33/agentic-awesome-skills
Evaluate agent behavior with versioned cases and explicit verifiers.
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Questions about Training Evaluation
What does Training Evaluation do?
Use Torch Points3D Hydra training, evaluation, Trainer, checkpoints, forward inference, visualization, and experiment-output helpers. Training Evaluation is an agent skill from VectorSpaceLab/AREX-Skill. Use Torch Points3D Hydra training, evaluation, Trainer, checkpoints, forward inference, visualization, and experiment-output helpers.
How do I install Training Evaluation in Claude Code?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation in VectorSpaceLab/AREX-Skill) into .claude/skills/training-evaluation in your project. Claude Code loads it when a task matches its description.
How do I install Training Evaluation in Codex?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a codex`. Or copy the skill folder (skills/repositories/repo-skills/torch-points3d/sub-skills/training-evaluation in VectorSpaceLab/AREX-Skill) into .agents/skills/training-evaluation in your project. Codex loads it when a task matches its description.
Can I use Training Evaluation in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add VectorSpaceLab/AREX-Skill --skill training-evaluation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/training-evaluation, .gemini/skills/training-evaluation, .github/skills/training-evaluation and .opencode/skills/training-evaluation in your project.
What does Training Evaluation need to run?
Going by SKILL.md and its folder, Training Evaluation needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Training Evaluation access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Training Evaluation safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Training Evaluation use?
Training Evaluation has a licence file (declared in SKILL.md) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Training Evaluation use?
About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4k tokens, read only when the agent opens those files.
What are the alternatives to Training Evaluation?
Skills that share tags, products or a category with Training Evaluation: Arize Evaluator (github/awesome-copilot, 40k stars), Ray Train Distributed Training (Orchestra-Research/AI-Research-SKILLs, 13k stars), Ito Training (affaan-m/ECC, 276k stars) and LLM Evaluation (davila7/claude-code-templates, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Training Evaluation?
VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 330 GitHub stars. The repository holds 159 skills in this directory. The repository was last updated on September 3, 2026.
Source: VectorSpaceLab/AREX-Skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.