anomalib

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 pipelines, including env var intermediary patterns, direct expression injection, dangerous sandbox configurations, and wildcard user allowlists. Use when reviewing workflow files that invoke AI coding agents, auditing CI/CD pipeline security for prompt injection risks, or evaluating agentic action configurations.

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.

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.

Reviews anomalib docstrings, documentation updates, and changelog expectations

Keep anomalib model READMEs, docs pages, image assets, and benchmark/result references in sync

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 Use when model sample images are missing, outdated, or suspected to be invalid.

Reviews anomalib model, data, callback, metric, and CLI integration conventions

Reviews anomalib contributor workflow, PR title, branch naming, and quality gate expectations

Enforces Google-style Python docstrings for Python code

Reviews anomalib Python style, typing, imports, and public API conventions

Review/generate unit, integration, and regression test expectations

Review/generate third-party code attribution, licensing, and notice requirements