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Review/generate third-party code attribution, licensing, and notice requirements
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Basierend auf der SOC-Berufsklassifikation
| name | third-party-code |
| description | Review/generate third-party code attribution, licensing, and notice requirements |
Use this skill when reviewing or generating code that is copied from, adapted from, or substantially based on an external project.
Use this skill for licensing, attribution, notices, and repository bookkeeping around third-party-derived code.
third-party-programs.txt entry;LICENSE file is missing;third-party-programs.txt.LICENSE file in the relevant component or subtree.LICENSE file.LICENSE file.third-party-programs.txt if the tracked component, source, or licensing metadata changes.third-party-programs.txtsrc/**/LICENSEthird-party-programs.txt?LICENSE file with upstream attribution and license text?third-party-programs.txt.LICENSE file.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.