perf-analyze
perf-analyze is a Runtime diagnostics & profiling skill for AI agents, published by NVIDIA in the TensorRT-LLM repository on GitHub. Skillspace rates perf-analyze C (74/100) and it passed the safety scan; the rating is based on static analysis only.
Launch and operate this repo's perf-analyze workflow, which DIAGNOSES a TensorRT-LLM serving deployment without applying changes — benchmark at one concurrency or a Pareto curve of them (tok/s/user vs tok/s/gpu), analytical SOL projection on by default (via the internal-perf-sol-analysis skill), nsys + ncu per-kernel deep dive (via the perf-nsight-compute-analysis skill), and a report naming the single dominant bottleneck. Use when the user wants to analyze / profile / diagnose trtllm-serve performance (throughput, TTFT, TPOT, ITL, e2e latency) or says "run perf-analyze". To actually APPLY optimizations, use the perf-optimize workflow instead.
- Grade
- C
- Quality
- 74 / 100
- Safety
- Passed
- GitHub stars
- 14,613
Unproven: rated by static analysis only, not yet compared head-to-head.
Our two independent classifiers differ on this skill's category, so treat the placement as provisional.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 100 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Not checked yet
- Category is a classifier prediction; no model has read this skill 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
Skillspace indexes and rates this skill; it does not host or endorse it. Run third-party skills at your own risk.