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repo-development

repo-development

Guide safe MNE-Python repository maintenance and editing while preserving human review, public API, documentation, test, and changelog rules.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill 문서

GitHub

name: repo-development description: "Guide safe MNE-Python repository maintenance and editing while preserving human review, public API, documentation, test, and changelog rules." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

MNE-Python repository development router

Use this sub-skill when the user asks for MNE-Python repository maintenance: code edits, tests, documentation, public API exposure, changelog fragments, contributor workflow, import-location checks, deprecations, optional-dependency handling, or local CI-style troubleshooting.

Load order

  1. For safe edit/test/doc/changelog workflows and the AI-assistance policy, read references/contributor-workflows.md.
  2. For lazy public API stubs, API reference entries, docstring rules, cross-references, and public API checklists, read references/api-surface-and-docs.md.
  3. If a local check fails, read references/troubleshooting.md.
  4. When validating that import mne resolves to the checkout being edited, run or adapt scripts/check_mne_checkout.py in the maintainer environment.

Own these requests

  • Planning safe MNE-Python code edits with human review checkpoints required by the project AI policy.
  • Choosing focused local commands for tests, docstring checks, pre-commit, documentation builds, changelog checks, import nesting, and dataset availability.
  • Adding, moving, documenting, or deprecating public functions/classes/methods while keeping lazy-loader .pyi stubs, __all__, doc API pages, tests, and changelog fragments aligned.
  • Diagnosing failures caused by importing the wrong checkout, missing optional dependencies, unavailable testing/sample data, stale docs builds, changelog author names, docstring validation, deprecation warnings, or import-nesting regressions.
  • Inventorying maintainer helper scripts safely: use bundled helpers here when available; treat source release/GitHub/credential automation as excluded or human-only.

Route elsewhere

  • User data analysis, file loading, preprocessing, visualization, source modeling, statistics, decoding, simulation, CLI usage, dataset caching, and runtime MNE workflows belong to the analysis-oriented sibling sub-skills.
  • Release engineering, publishing, GitHub API actions, credential-bearing automation, and account/CI administration are outside this operating sub-skill unless the user provides an explicit human-supervised maintenance task.
  • Do not draft issue or PR comments as if they are ready to paste. Provide technical notes that a human contributor can review, understand, test, and rewrite under their own responsibility.

Operating rules

  • Treat AI-assisted repository changes as drafts. The human contributor must review, understand, test, and disclose any AI assistance before submission.
  • Do not submit or recommend submitting fully automated issues or pull requests. Do not produce unreviewed AI-generated PR descriptions or issue comments.
  • Prefer small, focused patches with matching tests and documentation. Avoid unrelated refactors.
  • Do not depend on the construction checkout or original evidence files at runtime. Source paths mentioned in references are provenance only; operate on the user's active MNE-Python checkout and the files in this skill subtree.
  • When source guidance conflicts, preserve the style of the edited file and ask the human maintainer before broad style changes.
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