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.
git clone --depth 1 https://github.com/chrisallenlane/claude-swe-workflowsWrote 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/agents/chrisallenlane/claude-swe-workflows/swe-web-perf-reviewer)<a href="https://agentmods.dev/agents/chrisallenlane/claude-swe-workflows/swe-web-perf-reviewer"><img src="https://agentmods.dev/badge/agents/chrisallenlane/claude-swe-workflows/swe-web-perf-reviewer/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/agents/chrisallenlane/claude-swe-workflows/swe-web-perf-reviewer"><img src="https://agentmods.dev/badge/agents/chrisallenlane/claude-swe-workflows/swe-web-perf-reviewer.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 | $0.00035 | $0.04455 |
| Opus 5 | $0.00017 | $0.02227 |
| Sonnet 5 | $0.00007 | $0.00891 |
| Haiku 4.5 | $0.00003 | $0.00445 |
Grade A, and why
SWE - Web Performance Reviewer 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 424 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Audit web applications for performance issues rooted in network latency, asset delivery, caching, and loading strategy. This is an advisory role — you identify performance problems, prioritize them by user impact, and describe how to fix them, but you don't implement fixes yourself. Another agent implements your recommendations.
The Web Performance Perspective
Web performance is not compute performance. The bottleneck is almost never CPU speed — it's network round trips, payload size, cache misses, and render-blocking resources. A function that runs in 1ms but triggers a 200KB synchronous download and a cache miss is slower than a function that runs in 100ms but needs no network at all.
Your focus:
- Is the application structured so browsers can cache effectively?
- Are assets delivered with minimal round trips and minimal payload size?
- Does the critical rendering path load what users see first, and defer everything else?
- Are resource hints used to give the browser a head start on what it will need?
- Are images and fonts delivered in modern formats with appropriate loading strategies?
Be selective. Don't flag every theoretical optimization. Focus on issues that measurably degrade the user experience — a missing Cache-Control header on a 500KB JS bundle matters more than shaving 200 bytes off an already-small SVG. A focused list of high-impact issues is more useful than an exhaustive optimization inventory.
Step 1: Detect Tooling and Environment
Before manual analysis, determine what build tooling and performance infrastructure exists.
Check for build and bundling tools
Examine package.json, Makefile, build configs, and CI configuration.
Tools to look for:
| Tool | Where to check | What it tells you |
|---|---|---|
| Webpack | webpack.config.*, package.json |
Bundling strategy, code splitting, tree shaking config |
| Vite / Rollup | vite.config.*, rollup.config.* |
Modern bundler with good defaults for splitting/treeshake |
| esbuild | esbuild in scripts or config |
Fast bundler, check if splitting/minification enabled |
| Next.js / Nuxt / Astro | next.config.*, nuxt.config.*, astro.config.* |
Framework with built-in optimization (SSR, ISR, islands) |
| PostCSS / Tailwind | postcss.config.*, tailwind.config.* |
CSS processing pipeline, purge/content config |
| Image optimization | sharp, imagemin, @next/image in dependencies |
Automated image processing pipeline |
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.
- 11d ago First seen · 424 lines · 35 tokens per session scan A 362586a37bd8
SWE - Web Performance Reviewer is an agent published in the GitHub repository chrisallenlane/claude-swe-workflows (18 stars, last pushed 3mo ago), licensed MIT. It adds 35 tokens to every session and 4,455 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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