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MLOps Prototyping CN

Structured Jupyter notebook prototyping with pipeline integrity

skill openclawclawhub Free

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Structured Jupyter notebook prototyping with pipeline integrity

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md, package.json, scripts/check-notebook.sh

Validation

Use the Yavira download entry.
Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

Download the package from Yavira.
Extract it into a folder your agent can access.
Paste one of the prompts below and point your agent at the extracted folder.

New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Open Send to Agent page Open JSON manifest Open Markdown brief

Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.0

Provenance

Publisher: guohongbin-git
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 7 sections Open source page

MLOps Prototyping 🔬

Create standardized, reproducible Jupyter notebooks.

1. Notebook Structure Check ✅

Validate notebook follows best practices: ./scripts/check-notebook.sh notebook.ipynb Checks for: H1 title Imports section Config/Constants Data loading Pipeline usage

2. Template 📝

Use this structure: Title & Purpose Imports (standard → third-party → local) Configs (all constants at top) Datasets (load, validate, split) Analysis (EDA) Modeling (use sklearn.pipeline.Pipeline) Evaluations (metrics on test data)

Quick Start

# Check your notebook ./scripts/check-notebook.sh my-notebook.ipynb # Follow structure in notebook # Use Pipeline for all transforms # Set RANDOM_STATE everywhere

Key Rules

✅ DO: Put all params in Config section Use sklearn.pipeline.Pipeline Split data BEFORE any transforms Set random_state everywhere ❌ DON'T: Magic numbers in code Manual transforms (use Pipeline) Fit on full dataset (data leakage)

Author

Converted from MLOps Coding Course

v1.0.0 (2026-02-18)

Initial OpenClaw conversion Added notebook checker

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

1 Docs1 Scripts1 Config

SKILL.md Primary doc
scripts/check-notebook.sh Scripts
package.json Config