vf-performance

A performance review and benchmarking guide for the Veryfront project. It focuses on finding slow code, excessive memory use, request delays, build-time problems, and unnecessarily large browser bundles.

In plain words
What is it for?
Use it before reviewing performance-sensitive changes or investigating slow requests, builds, rendering, data fetching, or module loading. It checks issues such as blocking input/output, repeated fetches, uncontrolled parallel work, and cache problems.
Why use it?
It encourages measuring current behavior before changing code, so optimizations address real bottlenecks and do not introduce regressions.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/veryfront/veryfront-code/vf-performance
Any agent
npx skills add veryfront/veryfront-code --skill vf-performance
Clone the repo
git clone --depth 1 https://github.com/veryfront/veryfront-code

Made for: Claude Code, Codex.

Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,358 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found 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.

ModelPer sessionOnce invoked
Fable 5 $0.00033 $0.02358
Opus 5 $0.00016 $0.01179
Sonnet 5 $0.00007 $0.00472
Haiku 4.5 $0.00003 $0.00236

Measured 2d ago against content hash 72749f891862, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

vf-performance 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 2d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

time curl -s -o /dev/null http://localhost:3000/
.claude/skills/vf-performance/SKILL.md · 300 lines

How it starts

The opening of the file, as written. The whole thing — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Veryfront Performance Review & Benchmark

Overview

This skill covers performance analysis across all layers of veryfront: runtime hot paths, request latency, build/compile time, and bundle size. Use it to identify regressions before they ship and to measure the impact of optimizations.

Core principle: Measure first, optimize second. Never optimize without a baseline.

When to Use

  • Before merging performance-sensitive PRs
  • When investigating latency complaints or slowdowns
  • After adding new middleware, transforms, or rendering paths
  • When modifying hot paths (SSR, data fetching, API routing, transforms)
  • When adding dependencies or changing build configuration

Part 1: Performance Review Checklist

Run through this checklist when reviewing code for performance. Flag items that apply.

Runtime Hot Paths

Pattern Risk Where to Check
Sync I/O in request path Blocks event loop API handlers, middleware, SSR
await in a loop (N+1) Multiplied latency Data fetchers, module loaders
Unbounded Promise.all Memory spike Batch operations, parallel fetches
Missing cache / cache miss storm Redundant work FileCache, module cache, transform cache
Regex on untrusted input ReDoS potential Route matching, content parsing
Large JSON.stringify/parse CPU spike per request Request/response serialization, SSR props
Module re-import on each request Startup cost repeated Worker script, dynamic imports
Unnecessary cloning Memory churn request.clone(), deep copies

Memory & Allocation

Pattern Risk Where to Check
Growing Map/Set without eviction Memory leak Caches, registries, module maps
Holding large buffers across requests Heap pressure SSR streams, file uploads
Closures capturing request scope Prevents GC Event handlers, callbacks
new TextEncoder() per call Allocation churn Use module-level singleton
Accumulating strings via += O(n^2) copying HTML building, log formatting

Read the full file on GitHub · 300 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.

  1. 2d ago First seen · 300 lines · 33 tokens per session scan A 72749f891862

Subscribe to this mod's changes

vf-performance is a skill published in the GitHub repository veryfront/veryfront-code (18 stars, last pushed 2d ago), licensed Apache-2.0. It adds 33 tokens to every session and 2,358 once invoked, about $0.0002 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 2026-08-30.

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