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ML Pipeline
by
Dan Repaci
· GitHub ↗
· v0.1.0
635
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0
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Install in OpenClaw
/install ml-pipeline
Description
Complete machine learning pipeline for trading: feature engineering, AutoML, deep learning, and financial RL. Use for automated parameter sweeps, feature cre...
Usage Guidance
This package appears coherent with its stated purpose and the included scripts operate on local files (validation, analysis, copying, reporting). Before installing or running: (1) review and run the scripts in a controlled environment (not against sensitive system directories), (2) if you plan to connect to external feature stores or AutoML services, supply credentials only via secure mechanisms and be aware the skill does not declare or manage them, (3) note the deployment script will copy files into whatever target path you provide (use a sandbox or container if unsure). If you need higher assurance, ask the author for provenance or run the code in an isolated VM/container.
Capability Analysis
Type: OpenClaw Skill
Name: ml-pipeline
Version: 0.1.0
The skill is classified as suspicious due to the broad `allowed-tools: Bash` permission declared in `SKILL.md`, which grants the AI agent the ability to execute arbitrary shell commands, posing a significant Remote Code Execution (RCE) vulnerability if the agent is compromised or given malicious instructions. Additionally, the `scripts/pipeline_deployment.py` script performs file system operations (copying and deleting files/directories) based on user-provided paths, which, while necessary for its stated purpose, could be misused for unauthorized file manipulation. There is no clear evidence of intentional malicious behavior within the provided code or documentation, but these capabilities represent significant security risks.
Capability Assessment
Purpose & Capability
The name/description (ML pipeline for trading) aligns with the included scripts and SKILL.md: data validation, feature engineering, AutoML orchestration, evaluation, feature-store integration (described), and deployment. The required resources (none declared) are reasonable for an instruction-only skill containing template scripts.
Instruction Scope
SKILL.md gives high-level, ML-specific guidance (leakage checks, CV, AutoML steps) and asks the agent to gather dataset and pipeline parameters. The bundled scripts operate on local files and directories (validate, analyze, copy, report). There are no instructions to read unrelated system files, harvest environment secrets, or exfiltrate data to external endpoints.
Install Mechanism
No install spec is present (instruction-only skill) and all code is bundled. This is the lower-risk model: nothing is downloaded or exec-installed during install.
Credentials
The skill declares no required env vars or credentials, which matches the bundled scripts (they do local file I/O only). SKILL.md mentions integrating with feature stores (Feast, Tecton) and AutoML libraries — those integrations would typically require credentials or external dependencies, but the skill does not request them. This is not necessarily malicious but means the agent will expect the user to provide any required service credentials or local configs at runtime.
Persistence & Privilege
always is false and the skill does not request persistent system-wide privileges. The deployment script writes to a target directory chosen at runtime and creates a .deployment.json and deployment_report.json in that target — expected behavior for a deployment utility. The skill does not modify other skills or global agent configuration.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install ml-pipeline - After installation, invoke the skill by name or use
/ml-pipeline - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
Major update: ml-pipeline skill is now a unified end-to-end ML pipeline for quantitative trading, consolidating eight previous skills.
- Combines feature engineering, AutoML, deep learning, and financial RL into one authoritative toolkit.
- Provides rigorous anti-leakage validation practices specific to time-series and financial data.
- Includes step-by-step guidance on feature creation, selection, transformation, and evaluation.
- Features templates for pipeline automation including AutoML configuration, cross-validation, and deployment artifacts.
- Covers essential ML concepts (bias-variance, cross-validation) with emphasis on feature engineering decisions.
Metadata
Frequently Asked Questions
What is ML Pipeline?
Complete machine learning pipeline for trading: feature engineering, AutoML, deep learning, and financial RL. Use for automated parameter sweeps, feature cre... It is an AI Agent Skill for Claude Code / OpenClaw, with 635 downloads so far.
How do I install ML Pipeline?
Run "/install ml-pipeline" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is ML Pipeline free?
Yes, ML Pipeline is completely free (open-source). You can download, install and use it at no cost.
Which platforms does ML Pipeline support?
ML Pipeline is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created ML Pipeline?
It is built and maintained by Dan Repaci (@ahuserious); the current version is v0.1.0.
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