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/code-saurabh/openskills/benchmarknpx skills add CODE-SAURABH/OpenSkills --skill benchmarkgit clone --depth 1 https://github.com/CODE-SAURABH/OpenSkillsWhat 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 | $0.00062 | $0.02976 |
| Opus 5 | $0.00031 | $0.01488 |
| Sonnet 5 | $0.00012 | $0.00595 |
| Haiku 4.5 | $0.00006 | $0.00298 |
Grade A, and why
benchmark scanned grade A 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 yesterday.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
### Quick curl timing How it starts
The opening of the file, as written. The whole thing — 334 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Benchmark
Benchmarking without a baseline is noise. A benchmark that can't be reproduced is a guess. Every benchmark in this skill produces a number, a method, and a comparison — not an impression.
Performance is a feature. Regressions ship silently. This skill makes regressions visible before they reach users.
Benchmark Principles
- Measure before you optimize. An optimization without a before measurement is an assumption. Always baseline first.
- Reproduce exactly. A benchmark is only valid if another engineer can reproduce it with the same setup. Document the environment, the command, and the conditions.
- Medians lie. Use percentiles. P50 hides the users who are suffering. Always report P75, P95, and P99 alongside the median.
- Synthetic vs real-user data. Lighthouse in a lab tells you what's possible. RUM (Real User Monitoring) tells you what's happening. Use both.
- One change at a time. If two things change between benchmarks, you can't attribute the delta to either.
- A regression is a regression. A 10% slowdown on a fast page is still a regression. Set thresholds and enforce them.
Step 0: Establish the Baseline
Before any optimization or PR review, establish the baseline. Without it, "after" numbers are meaningless.
# Run Lighthouse baseline (3 runs, take median)
npx lighthouse https://your-app.com/key-page \
--output json \
--output-path ./baseline.json \
--chrome-flags="--headless" \
--throttling-method=simulate \
--preset=desktop
# Run 3 times and average — single runs are noisy
for i in 1 2 3; do
npx lighthouse https://your-app.com/key-page \
--output json \
--output-path "./baseline-run-$i.json" \
--chrome-flags="--headless"
done
Record in benchmark-baseline.md:
## Baseline — [Page/Endpoint] — [Date] — [Commit SHA]
| Metric | Run 1 | Run 2 | Run 3 | Median |
|--------|-------|-------|-------|--------|
| LCP | | | | |
| INP | | | | |
| CLS | | | | |
| FCP | | | | |
| TTFB | | | | |
| Total JS bundle | | | | |
| Total CSS bundle | | | | |
| Network requests | | | | |
**Environment:** macOS M2 / 6-core CPU throttle / Fast 3G simulation
**Tool:** Lighthouse 12.x / Chrome 124
**URL:** https://your-app.com/key-page
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.
- yesterday First seen · 334 lines · 62 tokens per session scan A 315c24f3990e
benchmark is a skill published in the GitHub repository CODE-SAURABH/OpenSkills (2 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 2,976 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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