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 rules/jy315189/everything-cursor/performancegit clone --depth 1 https://github.com/jy315189/everything-cursorWhat 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 | $0.00000 | $0.00390 |
| Opus 5 | $0.00000 | $0.00195 |
| Sonnet 5 | $0.00000 | $0.00078 |
| Haiku 4.5 | $0.00000 | $0.00039 |
Grade A, and why
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 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.
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.
What it actually says
Performance Rules
First Principles
- Measure before optimizing — profile, don't guess
- Correctness before performance — fast + wrong = useless
- Optimize the bottleneck — 80% of time is in 20% of code
Database
- No N+1 queries — use
include,join, or dataloader - Index every WHERE, JOIN, ORDER BY column — check query plans
- Paginate large result sets — cursor-based for >1000 rows
React
- useMemo / useCallback — ONLY when measured performance issue exists
- React.memo — ONLY for components that re-render often with same props
- Virtualize lists > 100 items — use @tanstack/react-virtual
- Lazy load heavy components —
React.lazy()+Suspense - Avoid re-render cascades — don't put frequently-changing state in Context
Network
- Batch API calls —
Promise.allfor independent requests - Cache server data — TanStack Query / SWR with appropriate staleTime
- Debounce user input — search, resize, scroll handlers (300ms default)
- Compress responses — gzip/brotli on server
Build
- Code split by route — dynamic
import()for route components - Tree-shake — use ESM, avoid barrel re-exports of large modules
- Optimize images — WebP/AVIF format, responsive sizes, lazy loading
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 · 41 lines · 0 tokens per session scan A a54714e8cee4
performance is a cursor rule published in the GitHub repository jy315189/everything-cursor (2 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 390 tokens. 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 2026-08-31.
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typescript
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python_lib
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