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slop-code-bench
slop-code-bench에는 SprocketLab에서 수집한 skills 9개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.
이 저장소의 skills
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].