Agent skill

Torchmetrics

by VectorSpaceLab in VectorSpaceLab/AREX-Skill

Use TorchMetrics to choose, inspect, and combine metric families for PyTorch evaluation, including core API, domain metrics, model-based metrics, and wrappers.

Apache-2.0Auto-check passedAI & LLM Engineering

Install Torchmetrics

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill torchmetrics -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill torchmetrics --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ 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/torchmetrics .claude/skills/torchmetrics && rm -rf skills-src

Use ~/.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/

Paste into Claude Code

Install the "torchmetrics" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torchmetrics into .claude/skills/torchmetrics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torchmetrics", 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

$skill-installer install https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torchmetrics

Type 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.

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill torchmetrics -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill torchmetrics --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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/torchmetrics .agents/skills/torchmetrics && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "torchmetrics" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torchmetrics into .agents/skills/torchmetrics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torchmetrics", 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.

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill torchmetrics -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill torchmetrics --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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/torchmetrics .cursor/skills/torchmetrics && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "torchmetrics" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torchmetrics into .cursor/skills/torchmetrics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torchmetrics", 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

$ gemini skills install https://github.com/VectorSpaceLab/AREX-Skill.git --path skills/repositories/repo-skills/torchmetrics

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill torchmetrics -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill torchmetrics --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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/torchmetrics .gemini/skills/torchmetrics && rm -rf skills-src

Use ~/.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/

Paste into Gemini CLI

Install the "torchmetrics" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torchmetrics into .gemini/skills/torchmetrics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torchmetrics", 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.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill torchmetrics

Installs 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).

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill torchmetrics -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ 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/torchmetrics .github/skills/torchmetrics && rm -rf skills-src

Use ~/.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/

Paste into GitHub Copilot

Install the "torchmetrics" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torchmetrics into .github/skills/torchmetrics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torchmetrics", 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.

skills CLI

$ npx skills add VectorSpaceLab/AREX-Skill --skill torchmetrics -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install VectorSpaceLab/AREX-Skill torchmetrics --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ 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/torchmetrics .opencode/skills/torchmetrics && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "torchmetrics" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/torchmetrics into .opencode/skills/torchmetrics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "torchmetrics", 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: torchmetrics
GitHub stars: 330
Token cost: ~964 tokens
SKILL.md length: 368 words
Files: 7 (incl. scripts, references)
Skills in repo: 159
Repo updated: Sep 3, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Use TorchMetrics to choose, inspect, and combine metric families for PyTorch evaluation, including core API, domain metrics, model-based metrics, and wrappers.

Works in 5 steps: If the task is about implementing or… → If the task names a familiar metric… → If the task is about combining metrics,… → …
Tasks that involve Deep learning
SKILL.md covers Start here, Route map, How to choose and Install guidance, plus 2 more sections
Runs Python scripts from its folder; calls python and pip

What it does

Torchmetrics is an agent skill from VectorSpaceLab/AREX-Skill. Use TorchMetrics to choose, inspect, and combine metric families for PyTorch evaluation, including core API, domain metrics, model-based metrics, and wrappers.

Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/metric-selection-cheatsheet.md`, `references/repo-provenance.md` and `references/repo-routing-metadata.json`).

It sits in AI & LLM Engineering, covering Deep learning. It works with PyTorch. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is Apache-2.0.

When your agent uses it

Tasks that involve Deep learning

Example prompts

“/torchmetrics”

Requirements

Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

If the task is about implementing or debugging a custom Metric, start with core-api.
If the task names a familiar metric family such as accuracy, F1, MSE, nDCG, or Cramer's V, use the sub-skill that owns that family.
If the task is about combining metrics, renaming outputs, tracking metrics over epochs, or plotting results, use…
If the metric may instantiate a pretrained model, feature extractor, or large optional asset, route to model-based-metrics.
If a request spans families, choose the primary metric family first, then follow the route back to core-api or…

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 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
- python
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.
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

Torchmetrics loads about 964 tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 43 tokens; SKILL.md has 368 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~43
When it runs · the whole SKILL.md, loaded when a task matches: ~964
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~3k

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

The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its Apache-2.0 licence (© VectorSpaceLab). 368 words, ~964 tokens.

Download SKILL.mdSave it as .claude/skills/torchmetrics/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.

name: torchmetrics
description: Use TorchMetrics to choose, inspect, and combine metric families for PyTorch evaluation, including core API, domain metrics, model-based metrics, and wrappers.
disable-model-invocation: true
metadata.disco-role: operating
license: Apache 2.0

TorchMetrics

TorchMetrics is a metric library for PyTorch evaluation. Use this skill when the request is about choosing, calling, combining, or debugging TorchMetrics APIs rather than about training a model itself.

Start here

Read references/metric-selection-cheatsheet.md to map a user request to the right sub-skill.
Run scripts/check_torchmetrics_environment.py with --device auto to confirm the install and core imports.
Read references/repo-provenance.md when you need freshness, source-version, or staleness checks.
Read references/troubleshooting.md when install, import, backend, device, distributed, plotting, or model-download problems appear.

Route map

core-api — Metric, functional versus module metrics, update / compute / forward / reset, custom metric state, Lightning logging, DDP behavior, persistence.
basic-metric-domains — classification, regression, retrieval, clustering, nominal, and other tensor-only metric families.
vision-detection-metrics — image quality, segmentation, detection, and panoptic metrics.
audio-text-metrics — audio and speech quality metrics plus no-download text metrics such as ROUGE, WER, CER, BLEU, SacreBLEU, and Perplexity.
model-based-metrics — BERTScore, InfoLM, CLIPScore, CLIP-IQA, FID/KID/LPIPS/DISTS/ARNIQA/PPL, DNSMOS, NISQA, VMAF, and similar metrics that need pretrained assets or external model planning.
collections-wrappers-plotting — MetricCollection, wrappers, trackers, and plotting.

How to choose

If the task is about implementing or debugging a custom Metric, start with core-api.
If the task names a familiar metric family such as accuracy, F1, MSE, nDCG, or Cramer's V, use the sub-skill that owns that family.
If the task is about combining metrics, renaming outputs, tracking metrics over epochs, or plotting results, use collections-wrappers-plotting.
If the metric may instantiate a pretrained model, feature extractor, or large optional asset, route to model-based-metrics.
If a request spans families, choose the primary metric family first, then follow the route back to core-api or collections-wrappers-plotting as needed.

Show full SKILL.md (102 more words)Show less

Install guidance

TorchMetrics has no verified console CLI. Install it from Python:

bash

pip install torchmetrics

Then add only the extra that matches the route you chose when needed, for example torchmetrics[audio], torchmetrics[image], torchmetrics[text], torchmetrics[detection], torchmetrics[multimodal], torchmetrics[video], torchmetrics[visual], or torchmetrics[clustering]. Avoid torchmetrics[all] unless you truly need a very broad evaluation environment.

Fast checks

python -c "import torchmetrics; print(torchmetrics.__version__)"
python scripts/check_torchmetrics_environment.py --device auto

Common signals

Metric, add_state, compute_with_cache, LightningModule, or DDP -> core-api
Accuracy, F1, MSE, nDCG, ClusterAccuracy, or CramersV -> basic-metric-domains
PSNR, DiceScore, MeanAveragePrecision, or PanopticQuality -> vision-detection-metrics
SNR, PESQ, WER, ROUGE, or Perplexity -> audio-text-metrics
BERTScore, CLIPScore, FID, LPIPS, DNSMOS, or VMAF -> model-based-metrics
MetricCollection, ClasswiseWrapper, MetricTracker, or .plot() -> collections-wrappers-plotting

Files

SKILL.md and 6 other files (scripts, references) in skills/repositories/repo-skills/torchmetrics of VectorSpaceLab/AREX-Skill.

SKILL.md
references/metric-selection-cheatsheet.md
references/repo-provenance.md
references/repo-routing-metadata.json
references/troubleshooting.md
scripts/check_torchmetrics_environment.py
sub-skills

Open the folder on GitHubat commit ac3fe1a

Compare with similar skills

Torchmetrics 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.

Torchmetrics compared with similar skills
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Torchmetrics this skillVectorSpaceLab/AREX-Skill	330	—	~964	Automated safety check: Pass	Apache-2.0	1 mo ago
Add Uint Supportpytorch/pytorch	104k	2 repos	~2.3k	Automated safety check: Pass	Custom licence	today
CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs	13k	7 repos	~1.7k	Automated safety check: Pass	MIT	3 mo ago
Add Torch Shapes Examplefacebook/pyrefly	7.1k	—	~1.3k	Automated safety check: Pass	MIT	today
MUSA GPU Training Optimizeropen-infra-skills/infra-skills	141	—	~1.7k	Automated safety check: Pass	Apache-2.0	3 mo ago
Ghstack CIpytorch/pytorch	104k	—	~1.4k	Automated safety check: Pass	Custom licence	today

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Questions about Torchmetrics

What does Torchmetrics do?

Use TorchMetrics to choose, inspect, and combine metric families for PyTorch evaluation, including core API, domain metrics, model-based metrics, and wrappers. Torchmetrics is an agent skill from VectorSpaceLab/AREX-Skill. Use TorchMetrics to choose, inspect, and combine metric families for PyTorch evaluation, including core API, domain metrics, model-based metrics, and wrappers.

When should I use Torchmetrics?

Torchmetrics fits situations like: tasks that involve Deep learning.

How do I install Torchmetrics in Claude Code?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill torchmetrics -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/torchmetrics in VectorSpaceLab/AREX-Skill) into .claude/skills/torchmetrics in your project. Claude Code loads it when a task matches its description.

How do I install Torchmetrics in Codex?

Run `npx skills add VectorSpaceLab/AREX-Skill --skill torchmetrics -a codex`. Or copy the skill folder (skills/repositories/repo-skills/torchmetrics in VectorSpaceLab/AREX-Skill) into .agents/skills/torchmetrics in your project. Codex loads it when a task matches its description.

Can I use Torchmetrics 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 torchmetrics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/torchmetrics, .gemini/skills/torchmetrics, .github/skills/torchmetrics and .opencode/skills/torchmetrics in your project.

What does Torchmetrics need to run?

Going by SKILL.md and its folder, Torchmetrics needs Python for the scripts in its folder and the command-line tools its instructions call (python and pip). Our summary lists: Python 3.

Does Torchmetrics access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Torchmetrics 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 Torchmetrics use?

Torchmetrics is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Torchmetrics use?

About 964 tokens (SKILL.md is roughly 3.9k 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 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Torchmetrics?

Skills that share tags, products or a category with Torchmetrics: Add Uint Support (pytorch/pytorch, 104k stars), CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars), Add Torch Shapes Example (facebook/pyrefly, 7.1k stars) and MUSA GPU Training Optimizer (open-infra-skills/infra-skills, 141 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Torchmetrics?

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.

Install Torchmetrics

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

TorchMetrics

Start here

Route map

How to choose

Install guidance

Fast checks

Common signals

Files

Compare with similar skills

Similar skills

More from VectorSpaceLab/AREX-Skill

Related

Questions about Torchmetrics