kaggle
- 21 skills
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- 4 hours ago last updated
- ▌ Review Docs 2 · kaggleAudit a game environment's README.md and AGENTS.md against its engine implementation (stale constants, unreachable caps, undocumented preconditions, wrong observation fields). Also use proactively after changing an environment engine that has sibling docs. The engine is the source of truth.
- ▌ Run Ablation 2 · kaggleRun a prompt-ablation study on a kaggle-environments game's LLM harness. Use when the user mentions "ablation", "prompt sensitivity", "test prompt variants", "compare prompts", "ablate the prompt", "prompt rewrite study", or asks whether their prompt wording is doing real work. Bootstraps a prompt_variants.py if missing, proposes new variants interactively, then runs a paired-seat tournament and reports the leaderboards.
- ▌ Create Harness 2 · kaggleCreate or update an LLM harness that connects a language model to a kaggle-environments game (prompt generation, response parsing, and tests)
- ▌ Review Harness 2 · kaggleReview an existing LLM harness for correctness and gameplay-impacting bugs (prompt accuracy, parser robustness, replay-archive scanning, cross-harness sweeps)
- ▌ Create Visualizer 2 · kaggleCreate or update a web visualizer for a Kaggle game environment (Vite + TypeScript frontend with replay playback)
- ▌ Create Environment 2 · kaggleCreate or update a Kaggle game environment (Python backend with specification, interpreter, renderer, agents, and tests)
- ▌ Onboard Open Spiel Game 2 · kaggleOnboard a new OpenSpiel game into kaggle-environments, including optional proxy, visualizer, and transformer
- ▌ Create Playable Visualizer 2 · kaggleBuild a standalone interactive (human vs AI) visualizer for a Kaggle game environment by porting the engine and bundled agents to TypeScript and running them in a web worker. Use after create-visualizer.
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- ▌ Kaggle CLI · kaggle bundleUse the local Kaggle CLI skill for command guidance, workflows, and troubleshooting across competitions, datasets, kernels/notebooks, models, model variations and versions, inbox file uploads, forums/discussions, benchmarks, configuration, OAuth/API-token authentication, and accelerator quota. Activate this skill when the user asks about kaggle CLI commands, examples, flags, metadata files, download/upload flows, submissions, benchmark tasks, or Kaggle CLI behavior.
- ▌ Hackathon Judging · kaggle bundleSteers Kaggle Hackathon hosts toward defensible LLM-assisted grading workflows collecting writeups and artifacts via the Kaggle MCP server, auditing with hamelsmu/evals-skills, and ranking submissions via pairwise comparisons / ELO with bell-curve adjustments. Use when a host wants to grade a public Kaggle Hackathon with help from LLMs or AI agents.
- ▌ Write Kaggle Benchmarks · kaggle bundleWrite, push, run, publish, and manage Kaggle Benchmark tasks using the kaggle CLI and the kaggle-benchmarks Python SDK. Use when the user wants to create or push a benchmark task (optionally with attached Kaggle datasets), run benchmarks against LLM models, check task/run status, stream or fetch execution logs, download results and source notebooks, publish a task to make it public, or troubleshoot benchmark workflows.
- ▌ Kaggle Standardized Agent Exam · kaggle bundleRegister as an agent on Kaggle, take a standardized exam, and earn a score.
- ▌ Review Docs · kaggleAudit a game environment's README.md and AGENTS.md against its engine implementation. Use when the user asks to "review", "audit", "check", or "fact-check" environment docs, when players report doc/engine discrepancies, or before a competition launch. Also use proactively after changing an environment's engine (`kaggle_environments/envs/<game>/<game>.py`) when a sibling README.md or AGENTS.md exists — rebalances and mechanic changes routinely leave those docs stale. The engine is always the source of truth — docs get fixed, not the engine.
- ▌ Run Ablation · kaggle bundleRun a prompt-ablation study on a kaggle-environments game's LLM harness. Use when the user mentions "ablation", "prompt sensitivity", "test prompt variants", "compare prompts", "ablate the prompt", "prompt rewrite study", or asks whether their prompt wording is doing real work. Bootstraps a prompt_variants.py if missing, proposes new variants interactively, then runs a paired-seat tournament and reports the leaderboards.
- ▌ Create Harness · kaggleCreate 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 Harness · kaggleReview 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.
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