Skill profile

tensorrt-llm

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency.

What this skill does for you

Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.

Quoted from the skill description in the pinned source

Who made it

Publisherdavila7

Repositoryclaude-code-templates

Installs358as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the tensorrt-llm skill from davila7/claude-code-templates.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 6af7cdf57b810aca5e544a0f695bf058f1c2a744. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 6af7cdf57b810aca5e544a0f695bf058f1c2a744. Raw findings: 2. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 6af7cdf57b810aca5e544a0f695bf058f1c2a744. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/davila7/claude-code-templates
Pinned skill file: View source at revision
Revision: 6af7cdf57b810aca5e544a0f695bf058f1c2a744
Package hash: sha256:b254d8395c267878eac17bf71c6825993d02f64d08f9f9bf93f99db724fe9341
Licence: MIT