synthetic-data-generation
synthetic-data-generation is a Fine-tuning & training data skill for AI agents, published by Red-Hat-AI-Innovation-Team in the sdg_hub repository on GitHub. Skillspace rates synthetic-data-generation F (45/100) and the safety scan rated it risky; the rating is based on static analysis only.
Risky. This skill has patterns associated with unsafe behaviour. Read the source carefully before running it.
Generate synthetic data using sdg_hub with composable blocks and YAML flows. Use when the user wants to create training datasets, generate QA pairs, run data generation pipelines, build custom flows, produce synthetic data from documents, use agent frameworks for data generation, or distill MCP tool-use traces. Supports pre-built flows, custom Python scripts, and YAML flow authoring with 20+ blocks, agent connectors (Langflow, LangGraph), MCP tool-use, and 100+ LLM providers via LiteLLM.
- Grade
- F
- Quality
- 45 / 100
- Safety
- Risky
- GitHub stars
- 152
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since.
Our review
- Architecture
- 100 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- High-risk patterns
- License
- Apache-2.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
What the scanner flagged
- references sensitive credential env
- mentions secrets in text
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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