Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/nvidia/tensorrt-llm/kernel-triton-writingnpx skills add NVIDIA/TensorRT-LLM --skill kernel-triton-writinggit clone --depth 1 https://github.com/NVIDIA/TensorRT-LLMWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nvidia/tensorrt-llm/kernel-triton-writing)<a href="https://agentmods.dev/skills/nvidia/tensorrt-llm/kernel-triton-writing"><img src="https://agentmods.dev/badge/skills/nvidia/tensorrt-llm/kernel-triton-writing.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00100 | $0.04229 |
| Opus 5 | $0.00050 | $0.02115 |
| Sonnet 5 | $0.00020 | $0.00846 |
| Haiku 4.5 | $0.00010 | $0.00423 |
Grade C, and why
kernel-triton-writing scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
| Kernel not updating after edit | Stale compilation cache | `rm -rf ~/.triton/cache/` | The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/api-core.md 10 KB
- references/api-language.md 12 KB
- references/concepts-semantics.md 7.7 KB
- references/operator-routing.md 4.3 KB
- references/patterns-advanced.md 11 KB
- references/patterns-basic.md 8.6 KB
- references/patterns-fusion.md 10 KB
- references/patterns-gemm.md 12 KB
- references/troubleshooting.md 11 KB
- scripts/__init__.py 684 B runs code
- scripts/benchmark_kernel.py 9.4 KB runs code
- scripts/verify_kernel.py 12 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 343 lines · 100 tokens per session scan C 5a379c6acccc
kernel-triton-writing is a skill published in the GitHub repository NVIDIA/TensorRT-LLM (14,505 stars, last pushed 5d ago), with no licence file. It adds 100 tokens to every session and 4,229 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
add-or-fix-type-checking
Fixes broken typing checks detected by ty, make typing, or make check-repo. Use when typing errors appear in local runs, CI, or PR logs.
sglang-diffusion-performance
Use when choosing the fastest SGLang Diffusion flags for a model, GPU, and VRAM budget.
add-jit-kernel
Step-by-step tutorial for adding a new lightweight JIT CUDA kernel to sglang's jitkernel module.
sglang-runtime-context
How SGLang's runtime configuration and process-global state are organized (RuntimeContext tiers, publish + namespace config bags, the pristine ServerArgs seed, override entry points, resource/stream/buffer leases, per-forward flags), the CI guardrails that enforce the design, and the idioms for developing and testing…
sglang-diffusion-add-model
Use when adding a new diffusion model or Diffusers pipeline to SGLang.
llm-torch-profiler-analysis
Unified LLM torch-profiler triage skill for sglang, vllm, TensorRT-LLM, and TokenSpeed. Use it to inspect an existing trace.json(.gz) or profile directory, or to drive live profiling against a running server when supported and return one three-table report with kernel, overlap-opportunity, and fuse-pattern tables.