Project Workflow
SkillDocs & knowledgeDevelop, test, and maintain this generated Python project using its recorded Copier choices and uv toolchain. Use for any code, dependency, configuration, documentation, or test change in this project, including simple libraries, CLIs, APIs, and layered AI or ML applications.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Project Workflow skill
What this skill tells your AI
The instructions your AI receives, as published by leynier/python-template in template/skills/project-workflow/SKILL.md and read by ahel’s review.
Use the generated project as the source of truth for its enabled layers.
Workflow
- Read
.copier-answers.yml,pyproject.toml, andreadme.mdbefore changing architecture or commands. - Preserve the
srclayout, public entry points, Python version, dependency groups, and existing user changes. - Add dependencies with
uv addoruv add --group dev; do not hand-edit the lockfile. - Keep secrets out of source control. Document required values in
.env.exampleand load them through the generated settings layer when present. - Add or update tests alongside behavior changes.
- Run
uv sync --all-groups,uv run ruff check .,uv run ruff format --check ., anduv run pytestbefore delivery. - If the project was created from a Git reference and needs upstream fixes, use
copier updateonly from a clean worktree and review the resulting diff carefully.
Entry Points
- For a library, verify imports and its public API.
- For a CLI, run its generated console command and a representative option.
- For an API or interface, start it locally and exercise the health or primary route.
- For MCP, agents, RAG, inference, training, or deployment, use the additional generated skill when present.
Signals
- GitHub stars
- 37
- Forks
- 1
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
project-workflow-leynier- Source
- github.com/leynier/python-template