by syda-ai · Agent Tool · ★ 98
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AI-powered synthetic data generation — structured tables, unstructured documents, multi-provider LLM support, referential integrity, and code-gen mode for millions of rows
| Stars | 98 |
| Forks | 8 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 52.0310638192928/100 |
| Open Issues | 2 |
| Last Updated | 2026-08-09 |
| Created | 2025-05-11 |
| Platforms | gemini, python |
| Est. Tokens | ~13k |
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syda is AI-powered synthetic data generation — structured tables, unstructured documents, multi-provider LLM support, referential integrity, and code-gen mode for millions of rows. It is categorized as a Agent Tool with 98 GitHub stars.
syda is primarily written in Python. It covers topics such as anthropic, codegen, data-generation.
You can find installation instructions and usage details in the syda GitHub repository at github.com/syda-ai/syda. The project has 98 stars and 8 forks, indicating an active community.
syda is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to syda on Agent Skills Hub include bridgic, WorkflowAI, pydantic-ai-backend. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: