en un clic
slop-code-bench
slop-code-bench contient 9 skills collectées depuis SprocketLab, avec une couverture métier par dépôt et des pages de détail sur le site.
Skills dans ce dépôt
Review checkpoint specs and tests to identify tests that encode ambiguous interpretations rather than explicit requirements. Use when asked to check checkpoint_N.md against test_checkpoint_N.py, when auditing tests for ambiguity, or when reviewing snapshot eval failures for interpretive issues.
Analyze checkpoint tests and suggest missing edge cases. Use after writing tests or when reviewing test coverage. Invoke with /edge-cases <problem> <checkpoint>.
Audit a checkpoint specification for realism and design decision forcing. Reviews specs to remove hand-holding, hidden corner cases, and architectural giveaways. Invoke with /audit-spec <problem> <checkpoint>.
Analyze checkpoint tests and suggest missing edge cases. Use after writing tests or when reviewing test coverage. Invoke with /edge-cases <problem> <checkpoint>.
Analyze test cases against specifications to find ambiguous assumptions. Use when tests might be making assumptions not explicitly defined in the spec. Invoke with /test-ambiguity-detector <problem> <checkpoint>.
Continually test and repair solutions to benchmark problems until they pass. Use when a solution has failing tests. Invoke with /fix-solution <snapshot_path> <problem_name> <checkpoint_index>.
Reclassify tests by adding @pytest.mark.functionality to tests not explicitly shown in the spec. Invoke with /reclassify-tests <problem> <checkpoint>.
Run problem tests using eval-snapshot instead of raw pytest. Use this to evaluate solutions against benchmark tests in Docker. Invoke with /run-tests <snapshot_path> <problem_name> <checkpoint_index>.
Validate all checkpoints from an agent run directory in parallel. Spawns test-validator agents for each checkpoint and summarizes results. Invoke with /validate-run <run_path> [problem].