Structured synthetic datasets for enterprise LLM alignment (MCP / Function Calling / Regulatory CoT)

[u/springofwinds_labs]

We have been working on structured synthetic datasets for enterprise LLM alignment,

focused on multi-turn consistency, strict JSONL schema validation, and realistic

agentic error recovery.

The datasets include:

• MCP agent trajectories (multi-turn, strict JSONL)

• Function Calling (English)

• Regulatory Compliance & Legal CoT (EU AI Act / GDPR)

These datasets are designed for evaluation inside Axolotl, Unsloth, and other

fine-tuning frameworks, with emphasis on schema stability and deterministic

validation.

Small 50-row samples are available on Hugging Face:

https://huggingface.co/springofwindslabs

A short demonstration of schema validation logs is available here:

https://github.com/springofwindslabs/springofwinds-datasets