Technology Selection
dotnet/skills
Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI (MEAI), Microsoft Agent Framework (MAF), GitHub Copilot SDK, ONNX…
Create efficient data pipelines with tf.data. An agent skill from TheBushidoCollective/han.
Install Tensorflow Data Pipelines
$ npx skills add TheBushidoCollective/han --skill tensorflow-data-pipelines -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install TheBushidoCollective/han tensorflow-data-pipelines --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/TheBushidoCollective/han.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines .claude/skills/tensorflow-data-pipelines && 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 "tensorflow-data-pipelines" agent skill from https://github.com/TheBushidoCollective/han/tree/main/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines into .claude/skills/tensorflow-data-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-data-pipelines", 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/TheBushidoCollective/han/tree/main/plugins/specialized/tensorflow/skills/tensorflow-data-pipelinesType 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 TheBushidoCollective/han --skill tensorflow-data-pipelines -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install TheBushidoCollective/han tensorflow-data-pipelines --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TheBushidoCollective/han.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines .agents/skills/tensorflow-data-pipelines && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "tensorflow-data-pipelines" agent skill from https://github.com/TheBushidoCollective/han/tree/main/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines into .agents/skills/tensorflow-data-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-data-pipelines", 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 TheBushidoCollective/han --skill tensorflow-data-pipelines -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install TheBushidoCollective/han tensorflow-data-pipelines --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TheBushidoCollective/han.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines .cursor/skills/tensorflow-data-pipelines && 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 "tensorflow-data-pipelines" agent skill from https://github.com/TheBushidoCollective/han/tree/main/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines into .cursor/skills/tensorflow-data-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-data-pipelines", 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/TheBushidoCollective/han.git --path plugins/specialized/tensorflow/skills/tensorflow-data-pipelines--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 TheBushidoCollective/han --skill tensorflow-data-pipelines -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install TheBushidoCollective/han tensorflow-data-pipelines --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TheBushidoCollective/han.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines .gemini/skills/tensorflow-data-pipelines && 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 "tensorflow-data-pipelines" agent skill from https://github.com/TheBushidoCollective/han/tree/main/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines into .gemini/skills/tensorflow-data-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-data-pipelines", 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 TheBushidoCollective/han tensorflow-data-pipelinesInstalls 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 TheBushidoCollective/han --skill tensorflow-data-pipelines -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/TheBushidoCollective/han.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines .github/skills/tensorflow-data-pipelines && 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 "tensorflow-data-pipelines" agent skill from https://github.com/TheBushidoCollective/han/tree/main/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines into .github/skills/tensorflow-data-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-data-pipelines", 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 TheBushidoCollective/han --skill tensorflow-data-pipelines -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install TheBushidoCollective/han tensorflow-data-pipelines --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/TheBushidoCollective/han.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines .opencode/skills/tensorflow-data-pipelines && 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 "tensorflow-data-pipelines" agent skill from https://github.com/TheBushidoCollective/han/tree/main/plugins/specialized/tensorflow/skills/tensorflow-data-pipelines into .opencode/skills/tensorflow-data-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tensorflow-data-pipelines", 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-data-pipelines- GitHub stars
- 198
- Used in
- 2 other repos
- Token cost
- ~4.4k tokens
- SKILL.md length
- 643 words
- Files
- 1
- Skills in repo
- 12
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Create efficient data pipelines with tf.data. An agent skill from TheBushidoCollective/han.
- Works in 12 steps: Always use prefetch() - Add… → Use num_parallel_calls=AUTOTUNE - Let… → Cache after expensive operations - Place… → …
- Tasks that involve Data pipelines and ETL
- SKILL.md covers Dataset Creation, Data Transformation, Batching and Shuffling and Performance Optimization, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Tensorflow Data Pipelines is an agent skill from TheBushidoCollective/han. Create efficient data pipelines with tf.data
Its SKILL.md is about 4.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Data pipelines and ETL and Deep learning. It works with TensorFlow. The repository describes itself as: A curated marketplace of Claude Code plugins that embody the principles of ethical and professional software development.
When your agent uses it
- Tasks that involve Data pipelines and ETL
- Tasks that involve Deep learning
Example prompts
- “/tensorflow-data-pipelines”
Requirements
- Python 3
- Pre-approved tools (allowed-tools): Bash, Read
Workflow steps
12 steps, taken from the first numbered list in SKILL.md.
- Always use prefetch() - Add .prefetch(tf.data.AUTOTUNE) at the end of pipeline to overlap data loading with training
- Use num_parallel_calls=AUTOTUNE - Let TensorFlow automatically tune parallelism for map operations
- Cache after expensive operations - Place .cache() after preprocessing but before augmentation and shuffling
- Shuffle before batching - Call .shuffle() before .batch() to ensure random batches
- Use appropriate buffer sizes - Shuffle buffer should be >= dataset size for perfect shuffling, or at least several thousand
- Normalize data in pipeline - Apply normalization in map() function for consistency across train/val/test
- Batch after transformations - Apply .batch() after all element-wise transformations for efficiency
- Use drop_remainder for training - Set drop_remainder=True in batch() to ensure consistent batch sizes
- Leverage AUTOTUNE - Use tf.data.AUTOTUNE for automatic performance tuning instead of manual values
- Apply augmentation after caching - Cache deterministic preprocessing, apply random augmentation after
- Use interleave for file reading - Parallel file reading with interleave() for large multi-file datasets
- Repeat for infinite datasets - Use .repeat() for training datasets to avoid dataset exhaustion
What it can do on your machine
Read from SKILL.md and the folder at commit 19caa51. 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:
BashRead
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 python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
tensorflow.org
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 Data Pipelines loads about 4.4k tokens when it runs. Until then it costs about 18 tokens; SKILL.md has 643 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: 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: Bash, Read
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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 643 words (~4,438 tokens).
“Build efficient, scalable data pipelines using the tf.data API for optimal training performance. This skill covers dataset creation, transformations, batching, shuffling, prefetching, and advanced optimization techniques to maximize GPU/TPU utilization.”
- name
- tensorflow-data-pipelines
- allowed-tools
- Bash, Read
Files
Just SKILL.md in plugins/specialized/tensorflow/skills/tensorflow-data-pipelines of TheBushidoCollective/han.
Open the folder on GitHubat commit 19caa51
Used in 2 other repositories
We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in TheBushidoCollective/han, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Tensorflow Data Pipelines 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 |
|---|---|---|---|---|---|---|
| Tensorflow Data Pipelines this skillTheBushidoCollective/han | 198 | 2 repos | ~4.4k | Automated safety check: Notes | Custom licence | |
| Technology Selectiondotnet/skills | 5.6k | 2 repos | ~2.1k | Automated safety check: Pass | MIT | |
| Ray Data for ML PipelinesOrchestra-Research/AI-Research-SKILLs | 13k | 3 repos | ~1.8k | Automated safety check: Pass | MIT | |
| ML Model Trainingsecondsky/claude-skills | 227 | 1 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Umap Learnjaechang-hits/SciAgent-Skills | 370 | — | ~4.7k | Automated safety check: Pass | BSD-3-Clause | |
| TensorBoard Training VisualizationOrchestra-Research/AI-Research-SKILLs | 13k | 3 repos | ~3.8k | Automated safety check: Pass | MIT |
Similar skills
- Official
Ray Data for ML Pipelines
Orchestra-Research/AI-Research-SKILLs
Uses Ray Data to read, transform and write large datasets across a cluster for ML training and batch inference, with streaming execution and optional GPU steps.
ML Model Training
secondsky/claude-skills
Train ML models with scikit-learn, PyTorch, TensorFlow. An agent skill from secondsky/claude-skills.
Umap Learn
jaechang-hits/SciAgent-Skills
UMAP dimensionality reduction for visualization, clustering prep, and feature engineering.
TensorBoard Training Visualization
Orchestra-Research/AI-Research-SKILLs
Covers logging and viewing training metrics, histograms, model graphs, embeddings and profiles with TensorBoard in PyTorch and TensorFlow projects.
Formatting
brendanhasz/probflow
Ensure consistent code formatting using the uv package manager and pre-commit.
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Works with
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Questions about Tensorflow Data Pipelines
What does Tensorflow Data Pipelines do?
Create efficient data pipelines with tf.data. An agent skill from TheBushidoCollective/han. Tensorflow Data Pipelines is an agent skill from TheBushidoCollective/han.
When should I use Tensorflow Data Pipelines?
Tensorflow Data Pipelines fits situations like: tasks that involve Data pipelines and ETL; tasks that involve Deep learning.
How do I install Tensorflow Data Pipelines in Claude Code?
Run `npx skills add TheBushidoCollective/han --skill tensorflow-data-pipelines -a claude-code`. Or copy the skill folder (plugins/specialized/tensorflow/skills/tensorflow-data-pipelines in TheBushidoCollective/han) into .claude/skills/tensorflow-data-pipelines in your project. Claude Code loads it when a task matches its description.
How do I install Tensorflow Data Pipelines in Codex?
Run `npx skills add TheBushidoCollective/han --skill tensorflow-data-pipelines -a codex`. Or copy the skill folder (plugins/specialized/tensorflow/skills/tensorflow-data-pipelines in TheBushidoCollective/han) into .agents/skills/tensorflow-data-pipelines in your project. Codex loads it when a task matches its description.
Can I use Tensorflow Data Pipelines 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 TheBushidoCollective/han --skill tensorflow-data-pipelines -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-data-pipelines, .gemini/skills/tensorflow-data-pipelines, .github/skills/tensorflow-data-pipelines and .opencode/skills/tensorflow-data-pipelines in your project.
What does Tensorflow Data Pipelines need to run?
SKILL.md names no scripts, command-line tools or credentials: Tensorflow Data Pipelines is instructions for the agent only. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Bash, Read.
Does Tensorflow Data Pipelines access the network?
SKILL.md names 1 domain. As links in the text: tensorflow.org. This is read from the text; nothing was executed.
Is Tensorflow Data Pipelines 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 Data Pipelines use?
Tensorflow Data Pipelines has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Tensorflow Data Pipelines use?
About 4.4k tokens (SKILL.md is roughly 18k 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 Data Pipelines?
Skills that share tags, products or a category with Tensorflow Data Pipelines: Technology Selection (dotnet/skills, 5.6k stars), Ray Data for ML Pipelines (Orchestra-Research/AI-Research-SKILLs, 13k stars), ML Model Training (secondsky/claude-skills, 227 stars) and Umap Learn (jaechang-hits/SciAgent-Skills, 370 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Tensorflow Data Pipelines?
TheBushidoCollective (a GitHub organization) maintains it in TheBushidoCollective/han, which has 198 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 8, 2026.
Source: TheBushidoCollective/han on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.