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Turn a two-sentence domain brief into an Unsloth-ready fine-tuning dataset. Eight-stage OpenRouter pipeline with LLM judge, human review and SFT / Alpaca / DPO / tool-calling / GRPO export. Runs in Docker.
Dataset-genie is an MCP server entry in ChatHome Skills, sourced from GitHub MCP Search and scored 44/100. Turn a two-sentence domain brief into an Unsloth-ready fine-tuning dataset. Eight-stage OpenRouter pipeline with LLM judge, human review and SFT / Alpaca / DPO. As a Model Context Protocol server, it exposes tools that MCP-compatible LLM clients such as Claude, Cursor, and Copilot can call directly, extending an agent's reach beyond its built-in capabilities. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding Dataset-genie to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
git clone https://github.com/k3nn3dy-ai/Dataset-genie.gitReview the upstream source before running this command.
Scan coverage: Install metadata and repository README.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
{
"fullName": "k3nn3dy-ai/Dataset-genie"
}Turn a two-sentence domain brief into an Unsloth-ready fine-tuning dataset. Eight-stage OpenRouter pipeline with LLM judge, human review and SFT / Alpaca / DPO / tool-calling / GRPO export. Runs in Docker.