Python engineering checks

Use the existing project policy and runtime as authority. Answer routine syntax and small implementation questions directly; load a reference only for a concrete uncertainty or failure mode.

Work from the affected contract

1. Read affected callers and pyproject/tool configuration; establish supported Python/library versions and the intended behavior.
2. For type/lint repair, capture the current diagnostic, fix its cause with a focused change and preserve public/runtime behavior. A justified narrow suppression needs a reason; blanket disabling is not a repair.
3. For concurrency, trace task ownership, cancellation, cleanup and blocking calls. For performance, identify a representative workload and measure the relevant bottleneck.
4. Respect existing packaging/environment tools and dependency policy. For arrays, check shape/dtype/missingness/copy behavior; for Textual, inspect compose/mount/reactivity and event-loop ownership.
5. Run affected diagnostics and meaningful behavior checks. Record executed commands/results and unresolved compatibility or environment gaps.

Scope and completion

Deliver the requested change or explanation with necessary evidence. Do not introduce a tool migration, ML platform, complete test strategy or mandatory specialist handoff for a local Python repair. Use ML-production/LLM packs only for model-specific lifecycle questions.

Use the user’s existing intent and authorization. Ask only for missing information that materially changes the result; use additional reviewers when they address a concrete uncertainty. Treat unavailable checks as gaps rather than successful verification.

Focused references

Read only the relevant sections. These are optional technical references, not a required reading sequence or a checklist of artifacts to manufacture. Verify version-specific recipes against the installed toolchain.

Concern	Reference
Async Patterns and Concurrency	async-patterns-and-concurrency.md
Debugging and Profiling	debugging-and-profiling.md
ML Engineering Workflows	ml-engineering-workflows.md
Modern Python Syntax and Types	modern-syntax-and-types.md
Project Structure and Tooling	project-structure-and-tooling.md
Resolving Mypy Errors	resolving-mypy-errors.md
Scientific Computing Foundations	scientific-computing-foundations.md
Systematic Delinting	systematic-delinting.md
Testing and Quality	testing-and-quality.md
Textual TUI Development	textual-tui-development.md

Optional task entry points

• create-project-scaffold: Create project scaffold for the affected python engineering contract, with scoped source and verification evidence.
• delint: Delint for the affected python engineering contract, with scoped source and verification evidence.
• profile: Profile for the affected python engineering contract, with scoped source and verification evidence.
• typecheck: Typecheck for the affected python engineering contract, with scoped source and verification evidence.

Use a specialist agent for a bounded independent investigation or review when useful. Available roles: delinting-specialist, python-code-reviewer, refactoring-architect. No fixed reviewer count is required.