Audit Performance
SkillDev toolsUse when reviewing or auditing tenferro-rs code for performance rule violations: before merging changes that touch tensor kernels, graph/compiler planning, caches, GPU kernels, Faer integration, benchmarks, or examples, when a workload is unexpectedly slow, or when scanning the repository for latent performance anti-patterns. Static audit that reports violations of PERFORMANCE_TIPS.md with file and line and never claims a speedup or slowdown without measurement.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Audit Performance skill
What this skill tells your AI
The instructions your AI receives, as published by tensor4all/tenferro-rs in .agents/skills/audit-performance/SKILL.md and read by ahel’s review.
This is a thin launcher; it carries no rule content.
- Read
PERFORMANCE_TIPS.mdin full. ItsAudit Proceduresection defines the scope handling, theDetect/Fixhints, and the report format. - Take the argument as the scope:
fullfor the whole repository, otherwise the given paths. Without an argument, audit the current diff againstorigin/main. - Follow the audit procedure and report each finding as
file:line, thePERFORMANCE_TIPS.mdsection title, the evidence, and the remediation direction. - Findings are static rule violations, not measured regressions. Do not claim
a speedup or slowdown, and route any proposed optimization through the
Performance-Gated Experiment Protocol in
PERFORMANCE_TIPS.md.
Signals
- GitHub stars
- 77
- Forks
- 4
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
audit-performance- Source
- github.com/tensor4all/tenferro-rs