Menu

Individual skill

cdf-anomalygen

Use when running the CDF AnomalyGen pipeline over a defect dataset — mask placement, fine-tuning, synthetic defect-image generation (SDG), evaluation, quality refinement, and pseudo-labeling — even when the user names only one stage.

skills/cdf-anomalygen/SKILL.md

Read pinned source

Source commit 25340619336e89bcc40365c28bfe9e790430468e

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
No
Observed behavior
Network or broad shell
Last checked
Nov 2, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
3,889
Repository last updated
Nov 6, 2026
License
Apache-2.0

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Skill: cdf-anomalygen

## Purpose

AnomalyGen fine-tunes the frozen **Cosmos** base into an **anomaly-generation** model: given a clean
image + defect mask, it paints a realistic defect into that region (synthetic data for detectors).
Pick a mode, collect its params, run the steps — **all commands from the repo root.**

## When to Use This Skill

Use for the CDF AnomalyGen pipeline over a defect dataset — any single stage (mask placement,
fine-tuning, generation, evaluation, refinement, or pseudo-labeling) or the full run.

- "Run the AnomalyGen pipeline on phone_screen"