Credit Risk Data Cleaning
github/awesome-copilot
Cleans raw credit data and screens variables before loan modeling, dropping unstable, noisy or redundant features and writing an Excel report of every step.
Agent skill
Preprocessing Data With Automated Pipelines
by jeremylongshore in jeremylongshore/tons-of-skills-marketplace
Process automate data cleaning, transformation, and validation for ML tasks.
Install Preprocessing Data With Automated Pipelines
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-pipelines -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace preprocessing-data-with-automated-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/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/preprocessing-data-with-automated-pipelines .claude/skills/preprocessing-data-with-automated-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 "preprocessing-data-with-automated-pipelines" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/preprocessing-data-with-automated-pipelines into .claude/skills/preprocessing-data-with-automated-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "preprocessing-data-with-automated-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/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/preprocessing-data-with-automated-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 jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-pipelines -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace preprocessing-data-with-automated-pipelines --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/.curated/preprocessing-data-with-automated-pipelines .agents/skills/preprocessing-data-with-automated-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 "preprocessing-data-with-automated-pipelines" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/preprocessing-data-with-automated-pipelines into .agents/skills/preprocessing-data-with-automated-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "preprocessing-data-with-automated-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 jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-pipelines -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace preprocessing-data-with-automated-pipelines --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/.curated/preprocessing-data-with-automated-pipelines .cursor/skills/preprocessing-data-with-automated-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 "preprocessing-data-with-automated-pipelines" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/preprocessing-data-with-automated-pipelines into .cursor/skills/preprocessing-data-with-automated-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "preprocessing-data-with-automated-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/jeremylongshore/tons-of-skills-marketplace.git --path skills/.curated/preprocessing-data-with-automated-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 jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-pipelines -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jeremylongshore/tons-of-skills-marketplace preprocessing-data-with-automated-pipelines --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/.curated/preprocessing-data-with-automated-pipelines .gemini/skills/preprocessing-data-with-automated-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 "preprocessing-data-with-automated-pipelines" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/preprocessing-data-with-automated-pipelines into .gemini/skills/preprocessing-data-with-automated-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "preprocessing-data-with-automated-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 jeremylongshore/tons-of-skills-marketplace preprocessing-data-with-automated-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 jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-pipelines -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/.curated/preprocessing-data-with-automated-pipelines .github/skills/preprocessing-data-with-automated-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 "preprocessing-data-with-automated-pipelines" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/preprocessing-data-with-automated-pipelines into .github/skills/preprocessing-data-with-automated-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "preprocessing-data-with-automated-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 jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-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 jeremylongshore/tons-of-skills-marketplace preprocessing-data-with-automated-pipelines --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/.curated/preprocessing-data-with-automated-pipelines .opencode/skills/preprocessing-data-with-automated-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 "preprocessing-data-with-automated-pipelines" agent skill from https://github.com/jeremylongshore/tons-of-skills-marketplace/tree/main/skills/.curated/preprocessing-data-with-automated-pipelines into .opencode/skills/preprocessing-data-with-automated-pipelines/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "preprocessing-data-with-automated-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
preprocessing-data-with-automated-pipelines- GitHub stars
- 2.8k
- Token cost
- ~1k tokens
- SKILL.md length
- 490 words
- Files
- 9 (incl. scripts, references, assets)
- Skills in repo
- 3,342
- Repo updated
- First seen
- Licence
- MIT
At a glance
Process automate data cleaning, transformation, and validation for ML tasks.
- Works in 4 steps: Analyze Requirements: Claude analyzes… → Generate Pipeline Code: Based on the… → Execute Pipeline: The generated code is… → …
- Requesting preprocess data
- SKILL.md covers Overview, How It Works, When to Use This Skill and Examples, plus 7 more sections
- Runs Python scripts from its folder
What it does
Preprocessing Data With Automated Pipelines is an agent skill from jeremylongshore/tons-of-skills-marketplace. Process automate data cleaning, transformation, and validation for ML tasks. Use when requesting "preprocess data", "clean data", "ETL pipeline", or "data transformation". Trigger with relevant phrases based on skill purpose.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts, reference files and assets (for example `assets/README.md`, `references/README.md` and `scripts/README.md`). Compatibility notes: Designed for Claude Code
It sits in Data & Analytics, covering Data cleaning and Data pipelines and ETL. It works with Python. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.
When your agent uses it
- Requesting preprocess data
- Data transformation
- With relevant phrases based on skill purpose
Example prompts
- “preprocess data”
- “clean data”
- “ETL pipeline”
- “/preprocessing-data-with-automated-pipelines”
Requirements
- Python 3
- Compatibility (from SKILL.md): Designed for Claude Code
- Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Glob, Bash(cmd:*)
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Analyze Requirements: Claude analyzes the user's request to understand the specific data preprocessing needs, including data sources…
- Generate Pipeline Code: Based on the requirements, Claude generates Python code for an automated data preprocessing pipeline using…
- Execute Pipeline: The generated code is executed, performing the data preprocessing steps.
- Provide Metrics and Insights: Claude provides performance metrics and insights about the pipeline's execution, including data quality…
What it can do on your machine
Read from SKILL.md and the folder at commit cfae287. 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:
ReadWriteEditGrepGlobBash(cmd:*)
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 5 files in scripts/ (Python), which the agent can run.
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.
Compatibility
Designed for Claude Code
From compatibility in the SKILL.md frontmatter.
Context cost
Preprocessing Data With Automated Pipelines loads about 1k tokens when it runs, and up to ~1k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 490 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 jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 490 words, ~1,022 tokens.
Download SKILL.mdSave it as
.claude/skills/preprocessing-data-with-automated-pipelines/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.- name
- preprocessing-data-with-automated-pipelines
- description
- Process automate data cleaning, transformation, and validation for ML tasks. Use when requesting "preprocess data", "clean data", "ETL pipeline", or "data transformation". Trigger with relevant phrases based on skill purpose.
- allowed-tools
- Read, Write, Edit, Grep, Glob, Bash(cmd:*)
- compatibility
- Designed for Claude Code
- version
- 1.23.0
- author
- Jeremy Longshore <jeremy@intentsolutions.io>
- license
- MIT
- tags
- ai, ml, etl
Data Preprocessing Pipeline
Construct and execute automated data preprocessing pipelines for cleaning, transforming, and validating ML-ready datasets.
Overview
construct and execute automated data preprocessing pipelines, ensuring data quality and readiness for machine learning. It streamlines the data preparation process by automating common tasks such as data cleaning, transformation, and validation.
How It Works
- Analyze Requirements: Claude analyzes the user's request to understand the specific data preprocessing needs, including data sources, target format, and desired transformations.
- Generate Pipeline Code: Based on the requirements, Claude generates Python code for an automated data preprocessing pipeline using relevant libraries and best practices. This includes data validation and error handling.
- Execute Pipeline: The generated code is executed, performing the data preprocessing steps.
- Provide Metrics and Insights: Claude provides performance metrics and insights about the pipeline's execution, including data quality reports and potential issues encountered.
When to Use This Skill
This skill activates when you need to:
- Prepare raw data for machine learning models.
- Automate data cleaning and transformation processes.
- Implement a robust ETL (Extract, Transform, Load) pipeline.
Examples
Example 1: Cleaning Customer Data
User request: "Preprocess the customer data from the CSV file to remove duplicates and handle missing values."
The skill will:
- Generate a Python script to read the CSV file, remove duplicate entries, and impute missing values using appropriate techniques (e.g., mean imputation).
- Execute the script and provide a summary of the changes made, including the number of duplicates removed and the number of missing values imputed.
Show full SKILL.md (240 more words)Show less
Example 2: Transforming Sensor Data
User request: "Create an ETL pipeline to transform the sensor data from the database into a format suitable for time series analysis."
The skill will:
- Generate a Python script to extract sensor data from the database, transform it into a time series format (e.g., resampling to a fixed frequency), and load it into a suitable storage location.
- Execute the script and provide performance metrics, such as the time taken for each step of the pipeline and the size of the transformed data.
Best Practices
- Data Validation: Always include data validation steps to ensure data quality and catch potential errors early in the pipeline.
- Error Handling: Implement robust error handling to gracefully handle unexpected issues during pipeline execution.
- Performance Optimization: Optimize the pipeline for performance by using efficient algorithms and data structures.
Integration
This skill can be integrated with other Claude Code skills for data analysis, model training, and deployment. It provides a standardized way to prepare data for these tasks, ensuring consistency and reliability.
Prerequisites
- Appropriate file access permissions
- Required dependencies installed
Instructions
- Invoke this skill when the trigger conditions are met
- Provide necessary context and parameters
- Review the generated output
- Apply modifications as needed
Output
The skill produces structured output relevant to the task.
Error Handling
- Invalid input: Prompts for correction
- Missing dependencies: Lists required components
- Permission errors: Suggests remediation steps
Resources
- Project documentation
- Related skills and commands
© jeremylongshore, MIT. 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 8 other files (scripts, references, assets) in skills/.curated/preprocessing-data-with-automated-pipelines of jeremylongshore/tons-of-skills-marketplace.
- SKILL.md
- assets/README.md
- assets/example_data.csv
- references/README.md
- scripts/README.md
- scripts/handle_errors.py
- scripts/pipeline.py
- scripts/transform_data.py
- scripts/validate_data.py
Open the folder on GitHubat commit cfae287
Compare with similar skills
Preprocessing Data With Automated 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 |
|---|---|---|---|---|---|---|
| Preprocessing Data With Automated Pipelines this skilljeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~1k | Automated safety check: Pass | MIT | |
| Credit Risk Data Cleaninggithub/awesome-copilot | 40k | 1 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Authoritative Data Harvesteryushui2022/MathModel-Skill | 454 | 1 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Data Quality Frameworkswshobson/agents | 40k | 11 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Bio Batch ProcessingGPTomics/bioSkills | 1.2k | 1 repos | ~3k | Automated safety check: Pass | MIT | |
| Data Cleaningmagnus919/agent-skills | 115 | — | ~2.1k | Automated safety check: Pass | MIT |
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Categories
Questions about Preprocessing Data With Automated Pipelines
What does Preprocessing Data With Automated Pipelines do?
Process automate data cleaning, transformation, and validation for ML tasks. Preprocessing Data With Automated Pipelines is an agent skill from jeremylongshore/tons-of-skills-marketplace. Process automate data cleaning, transformation, and validation for ML tasks.
When should I use Preprocessing Data With Automated Pipelines?
Preprocessing Data With Automated Pipelines fits situations like: requesting preprocess data; data transformation; with relevant phrases based on skill purpose.
How do I install Preprocessing Data With Automated Pipelines in Claude Code?
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-pipelines -a claude-code`. Or copy the skill folder (skills/.curated/preprocessing-data-with-automated-pipelines in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/preprocessing-data-with-automated-pipelines in your project. Claude Code loads it when a task matches its description.
How do I install Preprocessing Data With Automated Pipelines in Codex?
Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-pipelines -a codex`. Or copy the skill folder (skills/.curated/preprocessing-data-with-automated-pipelines in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/preprocessing-data-with-automated-pipelines in your project. Codex loads it when a task matches its description.
Can I use Preprocessing Data With Automated 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 jeremylongshore/tons-of-skills-marketplace --skill preprocessing-data-with-automated-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/preprocessing-data-with-automated-pipelines, .gemini/skills/preprocessing-data-with-automated-pipelines, .github/skills/preprocessing-data-with-automated-pipelines and .opencode/skills/preprocessing-data-with-automated-pipelines in your project.
What does Preprocessing Data With Automated Pipelines need to run?
Going by SKILL.md and its folder, Preprocessing Data With Automated Pipelines needs Python for the scripts in its folder. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(cmd:*). Compatibility (from SKILL.md): Designed for Claude Code.
Does Preprocessing Data With Automated Pipelines 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 Preprocessing Data With Automated Pipelines 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 Preprocessing Data With Automated Pipelines use?
Preprocessing Data With Automated Pipelines is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Preprocessing Data With Automated Pipelines use?
About 1k tokens (SKILL.md is roughly 4.1k 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 18 tokens, read only when the agent opens those files.
What are the alternatives to Preprocessing Data With Automated Pipelines?
Skills that share tags, products or a category with Preprocessing Data With Automated Pipelines: Credit Risk Data Cleaning (github/awesome-copilot, 40k stars), Authoritative Data Harvester (yushui2022/MathModel-Skill, 454 stars), Data Quality Frameworks (wshobson/agents, 40k stars) and Bio Batch Processing (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Preprocessing Data With Automated Pipelines?
jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.
Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.