ml-pipeline-workflow

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

0.98x

Quality

61%

Does it follow best practices?

Impact

73%

0.98x

Average score across 3 eval scenarios

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./tests/ext_conformance/artifacts/agents-wshobson/machine-learning-ops/skills/ml-pipeline-workflow/SKILL.md

The canonical home for this skill is ml-pipeline-workflow in wshobson/agents

Preview

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Run	Type	Date	Status
baseline vs usage-spec With / without context 7 months ago Completed	With / without context	7 months ago	Completed

Eval run

019cc841-6cf9-703c-a958-38d92b90633d

Run 7 months ago

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Repository: Dicklesworthstone/pi_agent_rust
Path: tests/ext_conformance/artifacts/agents-wshobson/machine-learning-ops/skills/ml-pipeline-workflow/SKILL.md
Commit: a65ce00

Evaluated: 7 months ago
Agent: Claude Code
Model: Claude Sonnet 4.6

Table of Contents

Customer Churn Prediction: Data Preparation Pipeline House Price Model: Reproducible Training Pipeline Fraud Detection Model: Safe Production Rollout

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