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.
Use this DeepCTR repo skill for CTR/recommender feature columns, Keras models, sequence/session models, multitask models, and legacy TensorFlow Estimator workflows.
Install Deepctr
$ npx skills add VectorSpaceLab/AREX-Skill --skill deepctr -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill deepctr --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/deepctr .claude/skills/deepctr && 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 "deepctr" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/deepctr into .claude/skills/deepctr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepctr", 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/deepctrType 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 deepctr -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill deepctr --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/deepctr .agents/skills/deepctr && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "deepctr" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/deepctr into .agents/skills/deepctr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepctr", 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 deepctr -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill deepctr --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/deepctr .cursor/skills/deepctr && 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 "deepctr" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/deepctr into .cursor/skills/deepctr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepctr", 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/deepctr--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 deepctr -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install VectorSpaceLab/AREX-Skill deepctr --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/deepctr .gemini/skills/deepctr && 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 "deepctr" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/deepctr into .gemini/skills/deepctr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepctr", 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 deepctrInstalls 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 deepctr -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/deepctr .github/skills/deepctr && 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 "deepctr" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/deepctr into .github/skills/deepctr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepctr", 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 deepctr -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 deepctr --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/deepctr .opencode/skills/deepctr && 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 "deepctr" agent skill from https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/deepctr into .opencode/skills/deepctr/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "deepctr", 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
deepctr- GitHub stars
- 328
- Token cost
- ~630 tokens
- SKILL.md length
- 237 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 159
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Use this DeepCTR repo skill for CTR/recommender feature columns, Keras models, sequence/session models, multitask models, and legacy TensorFlow Estimator workflows.
- Tasks that involve Deep learning
- SKILL.md covers Install and verify, Route by need, Read first and Common starting point, plus 1 more section
- Runs Python scripts from its folder; calls python
What it does
Deepctr is an agent skill from VectorSpaceLab/AREX-Skill. Use this DeepCTR repo skill for CTR/recommender feature columns, Keras models, sequence/session models, multitask models, and legacy TensorFlow Estimator workflows.
Its SKILL.md is about 630 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/installation-and-compatibility.md`, `references/repo-provenance.md` and `references/repo-routing-metadata.json`).
It sits in AI & LLM Engineering, covering Deep learning. It works with TensorFlow. 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
- “/deepctr”
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 1 file 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
Deepctr loads about 630 tokens when it runs, and up to ~2.4k if it reads all its reference files. Until then it costs about 43 tokens; SKILL.md has 237 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
The full file from VectorSpaceLab/AREX-Skill at commit ac3fe1a, republished under its Apache-2.0 licence (© VectorSpaceLab). 237 words, ~630 tokens.
Download SKILL.mdSave it as
.claude/skills/deepctr/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- deepctr
- description
- Use this DeepCTR repo skill for CTR/recommender feature columns, Keras models, sequence/session models, multitask models, and legacy TensorFlow Estimator workflows.
- disable-model-invocation
- true
- metadata.disco-role
- operating
- license
- Apache 2.0
DeepCTR
Use this repo skill when the task mentions DeepCTR, click-through-rate prediction, recommender models, sparse/dense feature columns, DIN/BST/DIEN/DSIN, multitask heads, or the legacy TensorFlow Estimator surface.
Install and verify
DeepCTR does not install TensorFlow for you. Install a TensorFlow build that matches your Python and platform, then install DeepCTR:
python -m pip install "numpy<2" "tensorflow<2.21"
python -m pip install deepctrIf you are using a TensorFlow 2.20-style stack with legacy Keras requirements, install the matching tf-keras package and set TF_USE_LEGACY_KERAS=1 before running DeepCTR. See references/installation-and-compatibility.md for compatibility notes.
Quick environment check:
python scripts/check_deepctr_env.py --jsonRoute by need
data-and-feature-columnsforSparseFeat,DenseFeat,VarLenSparseFeat, hashing, vocabulary paths, and input schema validation.keras-model-workflowsfor ordinary CTR/regression models, compile/fit/predict/save/load, and model selection.sequence-modelsfor DIN, BST, DIEN, DSIN,hist_/sess_naming, and sequence/session debugging.multitask-modelsfor SharedBottom, ESMM, MMOE, PLE, and multi-output target packing.estimator-workflowsfortf.estimator, TFRecord/Pandas input functions, and runtime gating.
Read first
- references/troubleshooting.md for cross-cutting install/import/version/GPU issues.
- references/repo-provenance.md when you need to check freshness or decide whether this skill is stale.
Common starting point
If the user has not specified a model family yet, start with data-and-feature-columns when the problem is input shaping, otherwise keras-model-workflows for single-output model choice.
What this skill does not do
- It does not tell you to open the original repository's examples or tests at runtime.
- It does not require a GPU unless the user explicitly asks for GPU or multi-GPU execution.
- It does not require Estimator workflows when
tf.estimatoris unavailable; in that case, use the Keras routes.
© 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
Files
SKILL.md and 6 other files (scripts, references) in skills/repositories/repo-skills/deepctr of VectorSpaceLab/AREX-Skill.
- SKILL.md
- references/installation-and-compatibility.md
- references/repo-provenance.md
- references/repo-routing-metadata.json
- references/troubleshooting.md
- scripts/check_deepctr_env.py
- sub-skills
Open the folder on GitHubat commit ac3fe1a
Compare with similar skills
Deepctr 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 |
|---|---|---|---|---|---|---|
| Deepctr this skillVectorSpaceLab/AREX-Skill | 328 | — | ~630 | Automated safety check: Pass | Apache-2.0 | |
| Ray Train Distributed TrainingOrchestra-Research/AI-Research-SKILLs | 13k | 3 repos | ~2.7k | Automated safety check: Pass | MIT | |
| TensorBoard Training VisualizationOrchestra-Research/AI-Research-SKILLs | 13k | 3 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Technology Selectiondotnet/skills | 5.6k | 2 repos | ~2.1k | Automated safety check: Pass | MIT | |
| ML Engineerdavila7/claude-code-templates | 32k | 9 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Sandbox Tfjsnodetool-ai/nodetool | 554 | — | ~660 | Automated safety check: Pass | AGPL-3.0 |
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Works with
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Questions about Deepctr
What does Deepctr do?
Use this DeepCTR repo skill for CTR/recommender feature columns, Keras models, sequence/session models, multitask models, and legacy TensorFlow Estimator workflows. Deepctr is an agent skill from VectorSpaceLab/AREX-Skill. Use this DeepCTR repo skill for CTR/recommender feature columns, Keras models, sequence/session models, multitask models, and legacy TensorFlow Estimator workflows.
When should I use Deepctr?
Deepctr fits situations like: tasks that involve Deep learning.
How do I install Deepctr in Claude Code?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill deepctr -a claude-code`. Or copy the skill folder (skills/repositories/repo-skills/deepctr in VectorSpaceLab/AREX-Skill) into .claude/skills/deepctr in your project. Claude Code loads it when a task matches its description.
How do I install Deepctr in Codex?
Run `npx skills add VectorSpaceLab/AREX-Skill --skill deepctr -a codex`. Or copy the skill folder (skills/repositories/repo-skills/deepctr in VectorSpaceLab/AREX-Skill) into .agents/skills/deepctr in your project. Codex loads it when a task matches its description.
Can I use Deepctr 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 deepctr -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/deepctr, .gemini/skills/deepctr, .github/skills/deepctr and .opencode/skills/deepctr in your project.
What does Deepctr need to run?
Going by SKILL.md and its folder, Deepctr needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Deepctr 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 Deepctr 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 Deepctr use?
Deepctr 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 Deepctr use?
About 630 tokens (SKILL.md is roughly 2.5k 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 1.8k tokens, read only when the agent opens those files.
What are the alternatives to Deepctr?
Skills that share tags, products or a category with Deepctr: Ray Train Distributed Training (Orchestra-Research/AI-Research-SKILLs, 13k stars), TensorBoard Training Visualization (Orchestra-Research/AI-Research-SKILLs, 13k stars), Technology Selection (dotnet/skills, 5.6k stars) and ML Engineer (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 Deepctr?
VectorSpaceLab (a GitHub organization) maintains it in VectorSpaceLab/AREX-Skill, which has 328 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.