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Automatically fix black code formatting issues in any Azure SDK for Python package
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | fix-black |
| description | Automatically fix black code formatting issues in any Azure SDK for Python package |
This skill automatically fixes black code formatting issues in any Azure SDK for Python package.
eng/tools/azure-sdk-tools[build]azpysdk --isolate black .git diffeng/black-pyproject.toml for repo-wide configurationAutomate updating the emitter package dependencies in eng/emitter-package.json for the Azure SDK for Python repository, then open a PR. Use this skill when the user wants to update @azure-tools/typespec-python (or any other dependency in emitter-package.json) to the latest version, create a PR for an emitter-package version bump, or manage emitter-package.json updates.
Emit the azure-ai-projects Python SDK from TypeSpec, apply post-emitter fixes, and create a Pull Request. WHEN: "emit SDK from TypeSpec", "generate azure-ai-projects SDK", "update azure-ai-projects from TypeSpec", "emit from TypeSpec", "regenerate azure-ai-projects". DO NOT USE FOR: other Azure SDK packages, manual code edits without TypeSpec. INVOKES: PostEmitter.ps1 script, git commands, gh CLI for PR creation.
Update CHANGELOG.md by comparing public APIs between the current branch and the latest released version on PyPI. WHEN: "update changelog", "generate changelog", "add changelog entry", "what changed in this version". DO NOT USE FOR: other Azure SDK packages. INVOKES: PyPI API, GitHub API (for tags), file operations.
Drafts concise team status updates with progress, plans, and blockers.
Create and test a classify-and-route Azure AI Content Understanding pipeline for packets that contain multiple document types (e.g. invoice + bank statement + loan application in one PDF). Walks per-type schema authoring → outer classifier wiring → batch test → category-aware stdout summary using the typed ContentUnderstandingClient. Use when the user has mixed-document packets.
Iteratively author and test a custom Azure AI Content Understanding analyzer for a folder of **document** files (PDFs, page images) of a single type. Walks layout extraction → schema authoring → validation → batch test → agent review → refine cycle using the typed ContentUnderstandingClient. Document modality only — audio, video, and image analyzers are planned for a later update. Use when the user wants to author a custom analyzer for invoices, contracts, forms, or any other single-type document set.