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SkillsMP hat 18 Skills aus open-edge-platform/anomalib gesammelt. Öffne einen Skill, um Quelle und Details zu prüfen.
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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/open-edge-platform/anomalib.Es werden 18 von 18 gesammelten Skills angezeigt.
Adds a new dataset/datamodule to anomalib under src/anomalib/data/. Use when wiring a new data source into the AnomalibDataset/AnomalibDataModule base classes, exporting it so anomalib.data.<Name> and the CLI/config (jsonargparse) can discover it, and adding…
Quellsprache: Englisch
Reviews anomalib model, data, callback, metric, and CLI integration conventions
Quellsprache: Englisch
Use when writing or updating Anomalib Studio UI component or hook tests that need the shared render/renderHook helpers, React Router paths or parameters, React Query, theme, URL-query, stream, suspense, or toast providers.
Quellsprache: Englisch
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches AI agents running in CI/CD…
Quellsprache: Englisch
Adds a new anomaly-detection model to anomalib under src/anomalib/models/. Use when implementing a new model architecture (image or video), wiring it into the AnomalibModule base class, registering it so get_model() and the CLI/config (jsonargparse) can…
Quellsprache: Englisch
Runs the anomalib benchmarking pipeline to train/evaluate a grid of model + dataset (+ category) combinations and collect metrics into a results CSV. Use when comparing multiple models/datasets/categories in one sweep, or authoring/editing a benchmark config…
Quellsprache: Englisch
Runs and configures the anomalib tiled-ensemble pipeline, which trains/evaluates one model per image tile and merges results (with optional seam smoothing) for high-resolution anomaly detection. Use when the user wants to train with image tiling, mentions…
Quellsprache: Englisch
Trains an anomalib model on a dataset via the Python API or CLI, including training on a custom folder-structured dataset with the Folder datamodule. Use when writing or debugging an anomalib training script/command, choosing Engine/Trainer arguments, or…
Quellsprache: Englisch
Designs and reviews REST APIs for FastAPI services using consistent resource naming, HTTP semantics, validation, security, and error handling patterns. Use for backend API tasks, endpoint design/refactors, or API review requests in FastAPI/Python projects.
Quellsprache: Englisch
Run or continue model benchmarks, collect measured results, and refresh README/docs benchmark sections from generated artifacts. Use when benchmark tables in model docs need to be created, updated, or corrected.
Quellsprache: Englisch
Reviews anomalib docstrings, documentation updates, and changelog expectations
Quellsprache: Englisch
Keep anomalib model READMEs, docs pages, image assets, and benchmark/result references in sync
Quellsprache: Englisch
Export, validate, and publish model sample-result images into docs/source/images and reference them from README/docs pages. Use when model sample images are missing, outdated, or suspected to be invalid.
Quellsprache: Englisch
Reviews anomalib contributor workflow, PR title, branch naming, and quality gate expectations
Quellsprache: Englisch
Enforces Google-style Python docstrings for Python code
Quellsprache: Englisch
Reviews anomalib Python style, typing, imports, and public API conventions
Quellsprache: Englisch
Review/generate unit, integration, and regression test expectations
Quellsprache: Englisch
Review/generate third-party code attribution, licensing, and notice requirements
Quellsprache: Englisch