Using oryxflow with Claude Code

Prefer to build oryxflow projects with an AI coding assistant instead of writing the task wiring yourself? There is an official Claude Code plugin, oryxflow, that sets up a ready-to-run project structure, wires tasks with @oryxflow.requires, and follows the house conventions automatically.

Install

/plugin marketplace add https://github.com/oryxintel/oryxflow-claude-plugin.git
/plugin install oryxflow@oryxflow

Commands

  • /oryxflow:init-project - set up a ready-to-run project structure in an empty directory, so you start writing tasks straight away instead of building the folders, files, and conventions by hand.

  • /oryxflow:init-gitlfs - put data/ under Git LFS, so you version and share your data as easily as your code — teammates clone the repo and get the exact datasets each run produced.

  • /oryxflow:update-project - bring an older project up to the current project structure, so you pick up the latest conventions and layout without a manual migration.

  • /oryxflow:check-standards - check names, style, and docstrings against the house standards, so the codebase stays consistent and easy for teammates (and the AI) to navigate and extend.

  • /oryxflow:migrate - restructure an existing ad-hoc analysis (monolithic notebooks, linear scripts, hardcoded paths) into a cached, parameterized oryxflow pipeline, one task at a time.

Once installed, the oryxflow skill auto-activates whenever you work in a oryxflow project (editing tasks.py / flow.py / run.py / cfg.py / flow_params.py).

Beyond scaffolding, the skill makes the agent a disciplined user of the cache: it starts every session with oryxflow.events.print_status() (pending warnings, last runs, recent failures), verifies after each code edit that the intended tasks actually reran (result.reasons / events.runs()) so a hash blind spot never passes silently, answers every staleness or expensive-recompute warning with the right exit (recompute / accept_code / pin — see Automatic code invalidation), and logs decision-relevant scalars via self.logger so they persist as task_log events across sessions. These are exactly the rules in the CLAUDE.md snippet — shipped as a skill so they load automatically and stay current with the library.

Learn more

This library is the engine the plugin drives; the full API is documented throughout the rest of these docs.