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/lisbeth718/pseo-skills/pseo-performancenpx skills add lisbeth718/pseo-skills --skill pseo-performancegit clone --depth 1 https://github.com/lisbeth718/pseo-skillsWrote 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/lisbeth718/pseo-skills/pseo-performance)<a href="https://agentmods.dev/skills/lisbeth718/pseo-skills/pseo-performance"><img src="https://agentmods.dev/badge/skills/lisbeth718/pseo-skills/pseo-performance.svg" alt="Measured on agentmods" 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 | $0.00069 | $0.02455 |
| Opus 5 | $0.00034 | $0.01228 |
| Sonnet 5 | $0.00014 | $0.00491 |
| Haiku 4.5 | $0.00007 | $0.00246 |
Grade A, and why
pseo-performance 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 5d 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
pSEO Performance Optimization
Optimize the application for fast builds, excellent Core Web Vitals, and reliable performance at 1000+ page scale.
Core Principles
- Static first: Pre-render as many pages as possible at build time
- Incremental where needed: Use ISR for pages that change frequently
- Minimal JavaScript: Pages should be functional with minimal client-side JS
- Image optimization: All images processed, sized, and lazy-loaded
- Cache aggressively: Cache data fetches, API calls, and rendered output
Optimization Areas
1. Static Generation Strategy
Choose the right rendering strategy for scale:
| Page Count | Strategy | Implementation |
|---|---|---|
| < 500 | Full SSG | Generate all pages at build time |
| 500-5000 | SSG + ISR | Generate high-traffic pages at build, ISR for rest |
| 5000+ | ISR + on-demand | Generate on first request, revalidate periodically |
Next.js App Router:
// Generate most important pages at build time
export async function generateStaticParams() {
const topPages = await getTopPages(500);
return topPages.map((p) => ({ slug: p.slug }));
}
// ISR for the rest
export const revalidate = 86400; // 24 hours
Fallback handling:
- Always configure a proper fallback (loading state, not blocking)
- Return
notFound()for genuinely invalid slugs - Set
dynamicParams = trueto allow ISR for pages not ingenerateStaticParams
2. Build Performance
For builds with many pages:
- Parallelize data fetching: Fetch all data once at the start, not per page
- Memoize data access: Use
React.cache()or module-level caching to avoid redundant reads - Limit build concurrency: If the build server has limited memory, configure worker limits
- Incremental builds: Use ISR to avoid rebuilding all pages on every deploy
- Monitor build time: Track build duration and set alerts for regressions
// Memoize INDEX-TIER data at module level (lightweight: slug, title, category)
// NEVER cache full page content this way — see section 7 Memory Management
import { cache } from "react";
export const getAllIndexData = cache(async () => {
// Returns PageIndex[] (~1KB per page) — safe to hold in memory
return fetchAllIndexDataFromSource();
});
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.
- 5d ago First seen · 253 lines · 69 tokens per session scan A 2d5f4f49677c
pseo-performance is a skill published in the GitHub repository lisbeth718/pseo-skills (53 stars, last pushed 7mo ago), licensed MIT. It adds 69 tokens to every session and 2,455 once invoked, about $0.0003 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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