// Review an existing LLM harness for correctness and gameplay-impacting bugs (prompt accuracy, parser robustness, replay-archive scanning, cross-harness sweeps)
| name | review-harness |
| description | Review an existing LLM harness for correctness and gameplay-impacting bugs (prompt accuracy, parser robustness, replay-archive scanning, cross-harness sweeps) |
Follow the instructions in .agents/skills/review-harness/SKILL.md.
Use $ARGUMENTS as the game name if provided.
Create or update an LLM harness that lets a language model play a kaggle-environments game. Use this skill whenever the user wants to write a harness, LLM agent, or game-playing prompt for any kaggle-environments game — including OpenSpiel games, word games, or custom environments. Also use it when the user mentions core_harness.py, GameHarness, ParseResult, or asks how to connect an LLM to a game.
Review an existing LLM harness for correctness and gameplay-impacting bugs. Use when the user asks to "review", "audit", "check", "look over", or "find bugs in" a harness, or asks whether a harness has issues that could affect win rates. Covers static code review (prompt accuracy, parser robustness, common anti-patterns), optional replay-archive scanning to quantify real-world impact, and an optional cross-harness sweep for the same anti-patterns.
Create or update an LLM harness that connects a language model to a kaggle-environments game (prompt generation, response parsing, and tests)
Create or update a Kaggle game environment (Python backend with specification, interpreter, renderer, agents, and tests)
Create or update a web visualizer for a Kaggle game environment (Vite + TypeScript frontend with replay playback)
Onboard a new OpenSpiel game into kaggle-environments, including optional proxy, visualizer, and transformer
