No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by zengxiao-he · LLM Plugin · ★ 579
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is tessera safe to install? View the security audit →
Tessera A small, from-scratch LLM stack built around one goal: distill a large teacher into a small student, then serve that student efficiently. Keeping that goal end-to-end means touching most of the pieces that matter in practice — custom GPU kernels, sharded training, an inference engine, quantization, and a serving front end — without any of it being a toy. It runs and is unit-tested on a laptop (CPU or Apple MPS). The Triton/CUDA kernels are written for NVIDIA GPUs; on anything else the model transparently falls back to a torch reference, and the kernels are checked against that reference whenever a GPU is available. What's in it Training side: Decoder transformer with RMSNorm, RoPE, grouped-query attention and SwiGLU ([](
| Stars | 579 |
| Forks | 9 |
| Language | Python |
| Category | LLM Plugin |
| Quality Score | 62.4904431562059/100 |
| Last Updated | 2026-06-05 |
| Created | 2026-06-05 |
| Platforms | python |
| Est. Tokens | ~7k |
These tools work well together with tessera for enhanced workflows:
Looking for a tessera alternative? If you're comparing tessera with other llm plugin tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
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tessera is From teacher to tiles — a from-scratch LLM distillation & serving engine: custom Triton/CUDA kernels, FSDP distillation, paged-KV continuous batching, speculative decoding, a Rust gateway, a JAX oracl. It is categorized as a LLM Plugin with 579 GitHub stars.
tessera is primarily written in Python. It covers topics such as cuda, flash-attention, fsdp.
You can find installation instructions and usage details in the tessera GitHub repository at github.com/zengxiao-he/tessera. The project has 579 stars and 9 forks, indicating an active community.
The top alternatives to tessera on Agent Skills Hub include ARIS-in-AI-Offer, J-Wash, aimirror. 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: