Borrowing it
Nothing to install: this file belongs to nguyenyou/scalex. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nguyenyou/scalex/main/.agents/skills/benchmark/SKILL.mdgit clone --depth 1 https://github.com/nguyenyou/scalexWrote 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/nguyenyou/scalex/benchmark)<a href="https://agentmods.dev/skills/nguyenyou/scalex/benchmark"><img src="https://agentmods.dev/badge/skills/nguyenyou/scalex/benchmark/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nguyenyou/scalex/benchmark"><img src="https://agentmods.dev/badge/skills/nguyenyou/scalex/benchmark.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00152 | $0.03562 |
| Opus 5.5 | $0.00061 | $0.01425 |
| Sonnet 5.5 | $0.00030 | $0.00712 |
| Haiku 4.5 | $0.00015 | $0.00356 |
Grade C, and why
benchmark 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 1mo 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.
rm -rf benchmark/scala3/.scalex How it starts
The opening of the file, as written. The whole thing — 367 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
Scalex has a multi-layered profiling and benchmarking system. Pick the right layer for the situation:
| Layer | Tool | When to use | Works in native? |
|---|---|---|---|
1. --timings |
Built-in flag | Quick phase breakdown, first look at any perf question | Yes |
| 2. hyperfine | bench.sh |
Reproducible before/after comparison with statistics | Yes |
| 3. async-profiler | profiling/profile.sh |
Deep CPU/alloc/lock flame graphs to find hotspots | JVM only |
| 4. JFR | profiling/scalex.jfc |
GC pressure, file I/O patterns, thread utilization | JVM only |
| 5. Microbenchmarks | src/bench.scala |
Isolate per-function cost with warmup + statistics | JVM only |
| 6. Memory profiling | bench.sh memory |
Heap usage, GC pressure, peak memory across scenarios | JVM only |
Decision guide
"Where is time spent?" → Start with --timings (Layer 1)
"Is this change faster?" → Use hyperfine before/after (Layer 2), optionally with bench-compare.sh
"Why is parsing slow?" → async-profiler CPU flame graph (Layer 3)
"Why are allocations high?" → async-profiler alloc or JFR ObjectAllocationSample (Layer 3/4)
"Is there GC pressure?" → JFR (Layer 4)
"How fast is extractSymbols on one file?" → Microbenchmark (Layer 5)
"How much memory does indexing use?" → Memory profiling (Layer 6)
"Is there a memory leak or GC regression?" → Memory profiling before/after (Layer 6)
Layer 1: --timings flag
The fastest way to see where time goes. Works in both JVM and native image. Prints to stderr.
# Cold index phase breakdown
rm -rf benchmark/scala3/.scalex
./scalex index benchmark/scala3 --timings
# Warm index
./scalex index benchmark/scala3 --timings
# Query with bloom/text-search breakdown
./scalex refs benchmark/scala3 Compiler --timings
# JVM mode
./mill run index benchmark/scala3 --timings
Phases reported
Index phases: git-ls-files, cache-load, oid-compare, parse, cache-save, and lazy build-* lookup phases
What ships with it
2 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.
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.
- 1mo ago Changed 714912226221
- 1mo ago First seen · 367 lines · 152 tokens per session scan C 667c86f31106
benchmark is a skill published in the GitHub repository nguyenyou/scalex (110 stars, last pushed 1mo ago), licensed MIT. It adds 152 tokens to every session and 3,562 once invoked, about $0.0006 per session on Opus 5.5. 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.
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