review
SolidAdversarially review a proposed or applied efficiency change to a training/evaluation pipeline: did the claimed mechanism actually engage, is the measurement still valid, what did it silently break. Use for `/parml:review`, "I made this training faster, check it", "review this diff before I merge it", "why did throughput improve but accuracy drop", "did this speedup actually work", or on any diff touching a training loop, data pipeline, optimiser, precision, or evaluation path. Walks a pitfall catalogue — score inflation, dead knobs, the throughput fallacy, optimisations that never engaged, stale step-unit hyperparameters, train/eval mismatch, leakage. Read-only; verdicts, not edits. Do NOT use to find new opportunities (that is /parml:audit) or for general code review of non-ML code (that is /code-review).
Install
Quality Score: 79/100
Skill Content
Details
- Author
- emaballarin
- Repository
- emaballarin/ccplugins
- Created
- 3 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Similar Skills
Semantically similar based on skill content — not just same category
review
Adversarial general purpose review mode.
pr-review
Deep review of someone else's pull request in an isolated worktree — hunts the failures that automated review misses (broken error paths, infinite loops, races, blast radius, claim-vs-code drift), deduplicates against the bot's comments, and gives a short verdict in chat. Read-only; never edits, pushes or posts.
fable-review
Adversarially review a change or artifact before it is locked in — try to break it, find the failure paths, rate severity — instead of confirming it looks fine. Use before merging/shipping/finalizing, or when the user says "review this", "poke holes", "what breaks", "find the weaknesses", "red-team it", "what did I miss". Finds and rates defects; does not rewrite. Pulled on demand; not always-on.