agentleFS
CliMACliMA/Oceananigans.jl/.claude/skills/run-tests/SKILL.md

run-tests

Skill1.4k starsChanged 10 days agoMITView on GitHub

Run targeted Oceananigans tests, prioritized by what's likely to break

48 other projects use a version of this, 1 of them edited.

Trending

More talk lately.about the whole repository

Dec 2025: 0 mentionsJan 2026: 2 mentionsFeb 2026: 2 mentionsMar 2026: 1 mentionApr 2026: 2 mentionsMay 2026: 0 mentionsJun 2026: 1 mentionJul 2026: 1 mentionAug 2026: 2 mentionsSep 2026: 1 mentionOct 2026: 4 mentionsNov 2026: 1 mention
Dec 2025Jun 2026Nov 2026
Mentions a month of the CliMA/Oceananigans.jl repository that our weekly crawl found. There is no adoption data for this file yet.

Most recently taken up by

Who's talking about CliMA/Oceananigans.jl

The biggest 5 of 45 mentions linking to the repository that our crawl found. Each line is their own headline.

See all 45

Talked about on GitHub, Bluesky and Hacker News (45 times).

On GitHub · 42

37 more on GitHub

Used with

Projects with it also use prepare-release, create-pr and 3 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • ShopifySkill

    prepare-release

    Prepare the changeset-release/main branch for release by syncing version.ts files and running pnpm install

    Also in 3 projects that use this

  • SentrySkill

    create-pr

    Create pull requests following Sentry conventions. Use when opening PRs, writing PR descriptions, or preparing changes for review. Follows Sentry's code review guidelines.

    Also in 4 projects that use this

  • SentrySkill

    commit

    Create commit messages following Sentry conventions. Use when committing code changes, writing commit messages, or formatting git history. Follows conventional commits with Sentry-specific issue references.

    Also in 4 projects that use this

  • MicrosoftSkill

    release

    Use ONLY when the user explicitly asks to cut/publish a Huabu desktop release or tag a version. Performs an outward action — bumps the version in apps/desktop/package.json, commits + annotated-tags vX.Y.Z, and pushes the branch + tag. That tag push auto-builds the macOS/Windows installers and publishes a GitHub Release. Provides `status`, `bump`, `tag-push`, and a one-command `run` (bump → tag-push).

    Also in 5 projects that use this

  • GoogleSkill

    code-review

    Adversarial systems, concurrency, memory-model, and architecture code review protocol. Use this skill whenever asked to review code, PRs, diffs, or branches in Filament.

    Also in 5 projects that use this

The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 5 are distinctive, and 2 are very specific to this project.

  • 0

    Common

    Most of the 44 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run targeted tests one-by-one, prioritized by what's most likely to fail given recent changes.

    line 8
  2. Distinctive:

    Never run the full test suite blindly — it's too large.

    line 9
  3. Distinctive:

    Look at the recent changes (staged, unstaged, or recent commits) and determine which test files are most likely affected.

    line 13
  4. Distinctive:

    Run a single test file on CPU:

    line 43
  5. Distinctive:

    If a test fails, fix the issue

    line 72
  6. Very specific:

    After direct tests pass, run unit/quality_assurance to catch import/doctest issues

    line 75
  7. Very specific:

    If Julia version issues arise, delete Manifest.toml and run Pkg.instantiate()

    line 82

“Common” is measured: kept by at least 6 in 10 of the 44 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Run Tests

Run targeted tests one-by-one, prioritized by what's most likely to fail given recent changes. Never run the full test suite blindly — it's too large. Fix each failure before moving on.

Step 1: Identify What Changed

Look at the recent changes (staged, unstaged, or recent commits) and determine which test files are most likely affected. Use this mapping:

Changed areaTests to run first (group/name = test/group/name.jl)
src/Grids/unit/grids, unit/grid_reconstruction
src/Fields/unit/field, abstract_operations/computed_field, unit/field_scans
src/Operators/unit/operators, unit/vector_rotation
src/BoundaryConditions/unit/boundary_conditions, time_stepping/boundary_conditions
src/Models/NonhydrostaticModels/time_stepping/nonhydrostatic_models, time_stepping/time_stepping
src/Models/HydrostaticFreeSurfaceModels/hydrostatic_free_surface/models, hydrostatic_free_surface/split_explicit_solver
src/Models/ShallowWaterModels/shallow_water/models
src/TimeSteppers/time_stepping/time_stepping, time_stepping/dynamics
src/TurbulenceClosures/turbulence_closures/turbulence_closures
src/Advection/time_stepping/immersed_advection, time_stepping/dynamics
src/BuoyancyFormulations/unit/buoyancy, time_stepping/seawater_density
src/Solvers/poisson_solvers/regular_grids, general_solvers/batched_tridiagonal
src/Simulations/simulation/simulations, simulation/diagnostics
src/OutputWriters/simulation/output_writers, simulation/jld2_writer, simulation/netcdf_writer
src/OutputReaders/simulation/output_readers
src/ImmersedBoundaries/unit/immersed_boundary_grid, hydrostatic_free_surface/immersed_boundaries
src/Coriolis/coriolis/coriolis
src/Forcings/time_stepping/forcings
src/Oceananigans.jl (exports)unit/quality_assurance
Docstrings, docs/src pagesdoctests/doctests (GPU only), unit/quality_assurance
ext/ (extensions)Corresponding <extension>/<extension> (e.g. makie/makie, metal/metal)

Step 2: Run the Most Likely Test First

Tests are selected by a prefix of their group/name and run in parallel worker processes. Run a single test file on CPU:

CUDA_VISIBLE_DEVICES=-1 TEST_ARCHITECTURE=CPU julia --project -e '
using Pkg
Pkg.test("Oceananigans"; test_args=["unit/grids"])
'

Or run a whole group if the changes span multiple areas:

CUDA_VISIBLE_DEVICES=-1 TEST_ARCHITECTURE=CPU julia --project -e '
using Pkg
Pkg.test("Oceananigans"; test_args=["unit", "--jobs=4", "--verbose"])
'

Pkg.test(; test_args=["--list"]) prints every test with its last measured duration. The groups are the directories under test/: unit, abstract_operations, coriolis, tripolar_grid, poisson_solvers, general_solvers, turbulence_closures, time_stepping, regression, hydrostatic_free_surface, vertical_coordinate, shallow_water, simulation, lagrangian_particles, multi_region, conservative_regridding, scripts, memory_allocation, init; and, only when selected explicitly, distributed, enzyme, reactant, sharding, metal, amdgpu, oneapi, makie, convergence. TEST_GROUP=unit is equivalent to test_args=["unit"].

Step 3: Fix and Iterate

  1. If a test fails, fix the issue
  2. Re-run the same test to confirm the fix
  3. Move on to the next most likely test
  4. After direct tests pass, run unit/quality_assurance to catch import/doctest issues

Notes

  • GPU tests may fail with "dynamic invocation error" — always test on CPU first
  • unit/quality_assurance checks explicit imports and Aqua.jl quality — run this for any change
  • test/mpi/ tests need 4 MPI ranks (MPI_TEST=true mpiexec -n 4 julia --project -e 'using Pkg; Pkg.test()' with TEST_GROUP=distributed) — skip unless changes touch src/DistributedComputations/
  • If Julia version issues arise, delete Manifest.toml and run Pkg.instantiate()

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.