Agent skill

Tensorflow Trainer

by majiayu000 in majiayu000/claude-skill-registry

TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.

MITAuto-check: notesAI & LLM Engineering

Install Tensorflow Trainer

skills CLI

$ npx skills add majiayu000/claude-skill-registry --skill tensorflow-trainer -a claude-code

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

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry tensorflow-trainer --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/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-ml/tensorflow-trainer .claude/skills/tensorflow-trainer && 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 "tensorflow-trainer" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-ml/tensorflow-trainer into .claude/skills/tensorflow-trainer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-trainer", 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/majiayu000/claude-skill-registry/tree/main/skills/ai-ml/tensorflow-trainer

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 majiayu000/claude-skill-registry --skill tensorflow-trainer -a codex

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

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry tensorflow-trainer --agent codex

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

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-ml/tensorflow-trainer .agents/skills/tensorflow-trainer && 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 "tensorflow-trainer" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-ml/tensorflow-trainer into .agents/skills/tensorflow-trainer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-trainer", 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 majiayu000/claude-skill-registry --skill tensorflow-trainer -a cursor

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

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry tensorflow-trainer --agent cursor

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

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-ml/tensorflow-trainer .cursor/skills/tensorflow-trainer && 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 "tensorflow-trainer" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-ml/tensorflow-trainer into .cursor/skills/tensorflow-trainer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-trainer", 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/majiayu000/claude-skill-registry.git --path skills/ai-ml/tensorflow-trainer

--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 majiayu000/claude-skill-registry --skill tensorflow-trainer -a gemini-cli

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

GitHub CLI

$ gh skill install majiayu000/claude-skill-registry tensorflow-trainer --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/majiayu000/claude-skill-registry.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-ml/tensorflow-trainer .gemini/skills/tensorflow-trainer && 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 "tensorflow-trainer" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-ml/tensorflow-trainer into .gemini/skills/tensorflow-trainer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-trainer", 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 majiayu000/claude-skill-registry tensorflow-trainer

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 majiayu000/claude-skill-registry --skill tensorflow-trainer -a github-copilot

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

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-ml/tensorflow-trainer .github/skills/tensorflow-trainer && 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 "tensorflow-trainer" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-ml/tensorflow-trainer into .github/skills/tensorflow-trainer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-trainer", 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 majiayu000/claude-skill-registry --skill tensorflow-trainer -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 majiayu000/claude-skill-registry tensorflow-trainer --agent opencode

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

Manual copy

$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-ml/tensorflow-trainer .opencode/skills/tensorflow-trainer && 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 "tensorflow-trainer" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-ml/tensorflow-trainer into .opencode/skills/tensorflow-trainer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-trainer", 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: tensorflow-trainer
GitHub stars: 666
Used in: 1 other repo
Token cost: ~937 tokens
SKILL.md length: 81 words
Files: 2
Skills in repo: 971
Repo updated: Oct 7, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.

Tasks that involve Deep learning
SKILL.md covers Overview, Capabilities, Target Processes and Tools and Libraries, plus 3 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
Tasks that involve Fine-tuning

What it does

Tensorflow Trainer is an agent skill from majiayu000/claude-skill-registry. TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.

Its SKILL.md is about 940 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It sits in AI & LLM Engineering, covering Deep learning and Fine-tuning. It works with TensorFlow. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

When your agent uses it

Tasks that involve Deep learning
Tasks that involve Fine-tuning

Example prompts

“/tensorflow-trainer”

Requirements

Pre-approved tools (allowed-tools): Read, Write, Bash, Glob, Grep

What it can do on your machine

Read from SKILL.md and the folder at commit 000116a. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
- Read
- Write
- Bash
- Glob
- Grep
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are json and javascript).
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

Tensorflow Trainer loads about 937 tokens when it runs. Until then it costs about 31 tokens; SKILL.md has 81 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~31
When it runs · the whole SKILL.md, loaded when a task matches: ~937

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
```
allowed-tools: Read, Write, Bash, Glob, Grep
```

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 000116a, republished under its MIT licence (© majiayu000). 81 words, ~937 tokens.

Download SKILL.mdSave it as .claude/skills/tensorflow-trainer/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.

name: tensorflow-trainer
description: TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.
allowed-tools: Read, Write, Bash, Glob, Grep

tensorflow-trainer

Overview

TensorFlow/Keras model training skill with callbacks, distributed strategies, TensorBoard integration, and production-ready model export capabilities.

Capabilities

Keras model training with callbacks
Custom training loops with tf.GradientTape
Distribution strategy configuration (MirroredStrategy, MultiWorkerMirroredStrategy, TPUStrategy)
TensorBoard logging and visualization
SavedModel export for TF Serving
TFLite conversion for edge deployment
Mixed precision training

Target Processes

Model Training Pipeline with Experiment Tracking
Distributed Training Orchestration
Model Deployment Pipeline

Tools and Libraries

TensorFlow
Keras
TensorBoard
TensorFlow Serving
TensorFlow Lite

Input Schema

json

{
  "type": "object",
  "required": ["modelConfig", "dataConfig", "trainingConfig"],
  "properties": {
    "modelConfig": {
      "type": "object",
      "properties": {
        "modelPath": { "type": "string" },
        "modelType": { "type": "string", "enum": ["sequential", "functional", "subclassed"] }
      }
    },
    "dataConfig": {
      "type": "object",
      "properties": {
        "trainPath": { "type": "string" },
        "valPath": { "type": "string" },
        "batchSize": { "type": "integer" },
        "prefetch": { "type": "boolean" }
      }
    },
    "trainingConfig": {
      "type": "object",
      "properties": {
        "epochs": { "type": "integer" },
        "optimizer": { "type": "string" },
        "learningRate": { "type": "number" },
        "loss": { "type": "string" },
        "metrics": { "type": "array", "items": { "type": "string" } },
        "callbacks": { "type": "array", "items": { "type": "string" } },
        "distributionStrategy": { "type": "string" }
      }
    },
    "exportConfig": {
      "type": "object",
      "properties": {
        "savedModelPath": { "type": "string" },
        "tflitePath": { "type": "string" },
        "servingSignatures": { "type": "array", "items": { "type": "string" } }
      }
    }
  }
}

Output Schema

json

{
  "type": "object",
  "required": ["status", "metrics", "modelPath"],
  "properties": {
    "status": {
      "type": "string",
      "enum": ["success", "error", "early_stopped"]
    },
    "metrics": {
      "type": "object",
      "properties": {
        "loss": { "type": "number" },
        "valLoss": { "type": "number" },
        "accuracy": { "type": "number" },
        "valAccuracy": { "type": "number" },
        "epochsTrained": { "type": "integer" }
      }
    },
    "modelPath": {
      "type": "string"
    },
    "savedModelPath": {
      "type": "string"
    },
    "tensorboardLogDir": {
      "type": "string"
    },
    "history": {
      "type": "object",
      "description": "Training history with all metrics per epoch"
    }
  }
}

Usage Example

javascript

{
  kind: 'skill',
  title: 'Train TensorFlow model',
  skill: {
    name: 'tensorflow-trainer',
    context: {
      modelConfig: {
        modelPath: 'models/cnn_model.py',
        modelType: 'functional'
      },
      dataConfig: {
        trainPath: 'data/train',
        valPath: 'data/val',
        batchSize: 64,
        prefetch: true
      },
      trainingConfig: {
        epochs: 50,
        optimizer: 'adam',
        learningRate: 0.001,
        loss: 'sparse_categorical_crossentropy',
        metrics: ['accuracy'],
        callbacks: ['early_stopping', 'model_checkpoint', 'tensorboard']
      }
    }
  }
}

Files

SKILL.md and 1 other file in skills/ai-ml/tensorflow-trainer of majiayu000/claude-skill-registry.

SKILL.md
metadata.json

Open the folder on GitHubat commit 000116a

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

a5c-ai/babysitterlibrary/specializations/data-science-ml/skills/tensorflow-trainer

Compare with similar skills

Tensorflow Trainer 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.

Tensorflow Trainer compared with similar skills
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Quaxnstarman/quax	143	—	~5.5k	Automated safety check: Pass	Apache-2.0	3 days ago
Ray Train Distributed TrainingOrchestra-Research/AI-Research-SKILLs	13k	3 repos	~2.7k	Automated safety check: Pass	MIT	3 mo ago
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TensorBoard Training VisualizationOrchestra-Research/AI-Research-SKILLs	13k	3 repos	~3.8k	Automated safety check: Pass	MIT	3 mo ago
nanoGPT Training GuideOrchestra-Research/AI-Research-SKILLs	13k	3 repos	~1.7k	Automated safety check: Pass	MIT	3 mo ago

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Questions about Tensorflow Trainer

What does Tensorflow Trainer do?

TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration. Tensorflow Trainer is an agent skill from majiayu000/claude-skill-registry. TensorFlow/Keras model training skill with callbacks, distributed strategies, and TensorBoard integration.

When should I use Tensorflow Trainer?

Tensorflow Trainer fits situations like: tasks that involve Deep learning; tasks that involve Fine-tuning.

How do I install Tensorflow Trainer in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill tensorflow-trainer -a claude-code`. Or copy the skill folder (skills/ai-ml/tensorflow-trainer in majiayu000/claude-skill-registry) into .claude/skills/tensorflow-trainer in your project. Claude Code loads it when a task matches its description.

How do I install Tensorflow Trainer in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill tensorflow-trainer -a codex`. Or copy the skill folder (skills/ai-ml/tensorflow-trainer in majiayu000/claude-skill-registry) into .agents/skills/tensorflow-trainer in your project. Codex loads it when a task matches its description.

Can I use Tensorflow Trainer 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 majiayu000/claude-skill-registry --skill tensorflow-trainer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tensorflow-trainer, .gemini/skills/tensorflow-trainer, .github/skills/tensorflow-trainer and .opencode/skills/tensorflow-trainer in your project.

What does Tensorflow Trainer need to run?

SKILL.md names no scripts, command-line tools or credentials: Tensorflow Trainer is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Bash, Glob, Grep.

Does Tensorflow Trainer 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 Tensorflow Trainer safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Tensorflow Trainer use?

Tensorflow Trainer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tensorflow Trainer use?

About 937 tokens (SKILL.md is roughly 3.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Tensorflow Trainer?

Skills that share tags, products or a category with Tensorflow Trainer: Quax (nstarman/quax, 143 stars), Ray Train Distributed Training (Orchestra-Research/AI-Research-SKILLs, 13k stars), ML Training Recipes (Orchestra-Research/AI-Research-SKILLs, 13k stars) and TensorBoard Training Visualization (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tensorflow Trainer?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 971 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Tensorflow Trainer

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

tensorflow-trainer

Overview

Capabilities

Target Processes

Tools and Libraries

Input Schema

Output Schema

Usage Example

Files

Used in 1 other repository

Compare with similar skills

Similar skills

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Related

Questions about Tensorflow Trainer