Use this sub-skill for MLflow Models, pyfunc, flavor APIs, signatures, input examples, dependencies, local serving/prediction, and mlflow.evaluate workflows.
$ npx skills add VectorSpaceLab/AREX-Skill --skill models-and-flavors -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill models-and-flavors --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/mlflow/sub-skills/models-and-flavors .claude/skills/models-and-flavors && 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 "models-and-flavors" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors into .claude/skills/models-and-flavors/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "models-and-flavors", 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/mlflow/sub-skills/models-and-flavorsType 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 models-and-flavors -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill models-and-flavors --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/mlflow/sub-skills/models-and-flavors .agents/skills/models-and-flavors && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "models-and-flavors" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors into .agents/skills/models-and-flavors/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "models-and-flavors", 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 models-and-flavors -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill models-and-flavors --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/mlflow/sub-skills/models-and-flavors .cursor/skills/models-and-flavors && 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 "models-and-flavors" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors into .cursor/skills/models-and-flavors/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "models-and-flavors", 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/mlflow/sub-skills/models-and-flavors--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 models-and-flavors -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill models-and-flavors --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/mlflow/sub-skills/models-and-flavors .gemini/skills/models-and-flavors && 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 "models-and-flavors" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors into .gemini/skills/models-and-flavors/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "models-and-flavors", 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 models-and-flavorsInstalls 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 models-and-flavors -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/mlflow/sub-skills/models-and-flavors .github/skills/models-and-flavors && 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 "models-and-flavors" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors into .github/skills/models-and-flavors/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "models-and-flavors", 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 models-and-flavors -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 models-and-flavors --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/mlflow/sub-skills/models-and-flavors .opencode/skills/models-and-flavors && 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 "models-and-flavors" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors into .opencode/skills/models-and-flavors/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "models-and-flavors", 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.
models-and-flavorsUse this sub-skill for MLflow Models, pyfunc, flavor APIs, signatures, input examples, dependencies, local serving/prediction, and mlflow.evaluate workflows.
Models And Flavors is an agent skill from VectorSpaceLab/AREX-Skill. Use this sub-skill for MLflow Models, pyfunc, flavor APIs, signatures, input examples, dependencies, local serving/prediction, and mlflow.evaluate workflows.
Its SKILL.md is about 680 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/api-reference.md`, `references/evaluation-and-serving.md` and `references/model-packaging.md`).
It sits in DevOps & Cloud. It works with MLflow. The repository describes itself as: A Skill Library for Automated Machine Learning. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit ac3fe1a. It shows what the files ask for, not the result of running them.
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.
Ships 2 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Models And Flavors loads about 675 tokens when it runs, and up to ~6.1k if it reads all its reference files. Until then it costs about 44 tokens; SKILL.md has 247 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.
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.
The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its Apache-2.0 licence (© VectorSpaceLab). 247 words, ~675 tokens.
.claude/skills/models-and-flavors/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.Use this sub-skill when the task involves packaging, loading, validating, evaluating, or locally serving MLflow Models.
MLmodel metadata.mlflow.pyfunc.PythonModel, callables, model-as-code files, artifacts, model_config, and params.mlflow.sklearn, mlflow.pytorch, mlflow.transformers, and mlflow.langchain when the issue is model packaging/loading rather than framework training.mlflow.evaluate, custom metrics/artifacts, model validation thresholds, and precomputed prediction evaluation.mlflow models CLI commands for local model serving, prediction, environment preparation, Dockerfile generation, Docker builds, and pip requirement updates.tracking-and-registry.serving-and-projects.genai-observability; use this sub-skill only for shared model packaging/evaluation mechanics.references/api-reference.md for concrete API signatures and call patterns.references/model-packaging.md for pyfunc, model-as-code, flavor, signature, and dependency packaging recipes.references/evaluation-and-serving.md for mlflow.evaluate, local scoring, and mlflow models CLI workflows.references/troubleshooting.md for schema mismatch, dependency, URI, optional-package, serving payload, and evaluation repair playbooks.Run these from any writable directory with MLflow installed:
python skills/mlflow/sub-skills/models-and-flavors/scripts/pyfunc_smoke.py
python skills/mlflow/sub-skills/models-and-flavors/scripts/evaluate_smoke.pyThe scripts use temporary local tracking directories and tiny fixtures only. They do not require network access, model registry services, optional deep-learning packages, or the MLflow source checkout.
© VectorSpaceLab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 6 other files (scripts, references) in skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors of VectorSpaceLab/AREX-Skill.
Open the folder on GitHubat commit ac3fe1a
Models And Flavors 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 |
|---|---|---|---|---|---|---|
| Models And Flavors this skillVectorSpaceLab/AREX-Skill | 331 | — | ~675 | Automated safety check: Pass | Apache-2.0 | |
| Google Agents CLI Observabilitypifferologo/cloud-agents-cli | 129 | 1 repos | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Osmo Lerobot Trainingmicrosoft/physical-ai-toolchain | 126 | — | ~3.8k | Automated safety check: Notes | MIT | |
| ML Pipeline ExpertJeffallan/claude-skills | 12k | — | ~1.9k | Automated safety check: Pass | MIT | |
| Senior ML Engineeralirezarezvani/claude-skills | 28k | 1 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Sync ML Reportsprobabl-ai/skills | 138 | — | ~1.6k | Automated safety check: Pass | BSD-3-Clause |
pifferologo/cloud-agents-cli
This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring…
microsoft/physical-ai-toolchain
Submit, monitor, analyze, and evaluate LeRobot imitation learning training jobs on OSMO with Azure ML MLflow integration and inference evaluation - Brought to you by microsoft/physical-ai-toolchain
Jeffallan/claude-skills
Designs ML pipeline infrastructure: experiment tracking with MLflow or Weights & Biases, Kubeflow and Airflow orchestration, Feast feature stores and model validation gates.
alirezarezvani/claude-skills
ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs.
probabl-ai/skills
Copy skore reports between local, Hub, and MLflow with skore sync, and optionally switch the recorded upload destination.
aiskillstore/marketplace
Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools.
VectorSpaceLab/AREX-Skill
Use this repo skill for Agent Lightning package tasks: authoring trainable agents, tracing rewards and spans, running LightningStore/Trainer loops, using agl CLI services, choosing examples, and…
VectorSpaceLab/AREX-Skill
A skill your agent uses when configuring LiteLLM for MCP tools, A2A agents, Claude Code/Cursor agent gateway traffic, MCP auth/OAuth, tool permissions, semantic filtering, or agent-specific proxy…
VectorSpaceLab/AREX-Skill
Build and debug DB-GPT agents, tools, skills, teams, and AWEL workflows, including deterministic local DAG runs and HTTP-trigger topology without assuming an LLM, credential, or external service.
VectorSpaceLab/AREX-Skill
Work on the actively maintained LangChain v1 agent package: initchatmodel, createagent, structured output, tools, middleware, embeddings initialization, provider routing, and agent runtime…
VectorSpaceLab/AREX-Skill
A skill your agent uses for giskard.agents async chat workflows, tools, prompt templates, structured outputs, retries, rate limiting, embeddings, and optional LiteLLM backend.
VectorSpaceLab/AREX-Skill
A skill your agent uses for AlphaFold 3 input preparation, prediction command planning, output interpretation, and Python API inspection.
Works with
Categories
Use this sub-skill for MLflow Models, pyfunc, flavor APIs, signatures, input examples, dependencies, local serving/prediction, and mlflow.evaluate workflows. Models And Flavors is an agent skill from VectorSpaceLab/AREX-Skill.evaluate workflows.
Models And Flavors fits situations like: devOps & Cloud work in your project.
Run `npx skills add VectorSpaceLab/AREX-Skill --skill models-and-flavors -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors in VectorSpaceLab/AREX-Skill) into .claude/skills/models-and-flavors in your project. Claude Code loads it when a task matches its description.
Run `npx skills add VectorSpaceLab/AREX-Skill --skill models-and-flavors -a codex`. Or copy the skill folder (skills/repositories/repo-skills/mlflow/sub-skills/models-and-flavors in VectorSpaceLab/AREX-Skill) into .agents/skills/models-and-flavors in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add VectorSpaceLab/AREX-Skill --skill models-and-flavors -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/models-and-flavors, .gemini/skills/models-and-flavors, .github/skills/models-and-flavors and .opencode/skills/models-and-flavors in your project.
Going by SKILL.md and its folder, Models And Flavors needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3; Docker.
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.
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.
Models And Flavors 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.
About 675 tokens (SKILL.md is roughly 2.7k 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 5.4k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Models And Flavors: Google Agents CLI Observability (pifferologo/cloud-agents-cli, 129 stars), Osmo Lerobot Training (microsoft/physical-ai-toolchain, 126 stars), ML Pipeline Expert (Jeffallan/claude-skills, 12k stars) and Senior ML Engineer (alirezarezvani/claude-skills, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 331 GitHub stars. The repository holds 157 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.
