A performance-measurement skill for creating baselines, spotting slowdowns after code changes, and comparing technology stacks. It measures web pages and APIs using browser-based tests and repeated requests.

Use it to check page loading and browser metrics, page and bundle sizes, network requests, API latency, response sizes, status codes, and behavior under concurrent load.

It replaces vague reports that something feels slow with comparable measurements. It helps reveal whether a change introduced a regression before launch.

benchmark — Skill for Claude Code and Codex by ufy2024/AuC

About the project

AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent workflow.

ufy2024/AuC · 1,067 stars · on GitHub

Install

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.

Any agent

npx skills add ufy2024/AuC --skill benchmark

Clone the repo

git clone --depth 1 https://github.com/ufy2024/AuC

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/ufy2024/auc/benchmark/github.svg)](https://agentmods.dev/skills/ufy2024/auc/benchmark)

Your own site

<a href="https://agentmods.dev/skills/ufy2024/auc/benchmark"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/ufy2024/auc/benchmark"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/benchmark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 25 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 719 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 1 finding, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

medium Agent Snooping · line 20
Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.

Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.

How audits are shown

Origin 84% copy Near-identical to another mod in the catalogue.

Token cost

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	$0.00025	$0.00719
Opus 5.5	$0.00010	$0.00288
Sonnet 5.5	$0.00005	$0.00144
Haiku 4.5	$0.00003	$0.00072

Measured 2mo ago against content hash a75c960bb402, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

benchmark scanned grade A with 0 findings 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 2mo 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.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

84% identical to benchmark — 26 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

auc/skill_library/bundled/benchmark/SKILL.md · 114 lines

How it starts

The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Benchmark — Performance Baseline & Regression Detection

When to Use

Before and after a PR to measure performance impact
Setting up performance baselines for a project
When users report "it feels slow"
Before a launch — ensure you meet performance targets
Comparing your stack against alternatives

How It Works

Mode 1: Page Performance

Measures real browser metrics via browser MCP:

1. Navigate to each target URL
2. Measure Core Web Vitals:
   - LCP (Largest Contentful Paint) — target < 2.5s
   - CLS (Cumulative Layout Shift) — target < 0.1
   - INP (Interaction to Next Paint) — target < 200ms
   - FCP (First Contentful Paint) — target < 1.8s
   - TTFB (Time to First Byte) — target < 800ms
3. Measure resource sizes:
   - Total page weight (target < 1MB)
   - JS bundle size (target < 200KB gzipped)
   - CSS size
   - Image weight
   - Third-party script weight
4. Count network requests
5. Check for render-blocking resources

Mode 2: API Performance

Benchmarks API endpoints:

1. Hit each endpoint 100 times
2. Measure: p50, p95, p99 latency
3. Track: response size, status codes
4. Test under load: 10 concurrent requests
5. Compare against SLA targets

Mode 3: Build Performance

Measures development feedback loop:

1. Cold build time
2. Hot reload time (HMR)
3. Test suite duration
4. TypeScript check time
5. Lint time
6. Docker build time

Mode 4: Before/After Comparison

Run before and after a change to measure impact:

/benchmark baseline    # saves current metrics
# ... make changes ...
/benchmark compare     # compares against baseline

Output:

| Metric | Before | After | Delta | Verdict |
|--------|--------|-------|-------|---------|
| LCP | 1.2s | 1.4s | +200ms | WARNING: WARN |
| Bundle | 180KB | 175KB | -5KB | ✓ BETTER |
| Build | 12s | 14s | +2s | WARNING: WARN |

Output

Stores baselines in .ecc/benchmarks/ as JSON. Git-tracked so the team shares baselines.

Integration

CI: run /benchmark compare on every PR
Pair with /canary-watch for post-deploy monitoring
Pair with /browser-qa for full pre-ship checklist

Read the full file on GitHub · 114 lines

Changes

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.

2mo ago First seen · 114 lines · 25 tokens per session scan A a75c960bb402

Subscribe to this mod's changes

benchmark is a skill published in the GitHub repository ufy2024/AuC (1,067 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 719 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 84% identical to benchmark, differing in 26 lines, and is treated as a copy.

Analytics and metrics

benchmark next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
benchmarkufy2024/AuC	Skill	1.1k	3mo ago	MIT	A	25	Claude Code, Codex
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code