performance-optimizer

A coding assistant focused on finding ways to make web applications run faster. It examines browser loading, server responses, databases, caching, and delivered code.

In plain words
What is it for?
Use it to investigate slow pages, delayed API responses, inefficient database queries, large bundles, and other web performance problems.
Why use it?
It helps locate slow parts of an application and choose targeted improvements instead of guessing. The input lists example performance measures and optimization areas.

Agent

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 agents/desilokesh1/antigravity-fullstack-hq/performance-optimizer
Clone the repo
git clone --depth 1 https://github.com/desilokesh1/antigravity-fullstack-hq
Per session 22 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 395 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. 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 $0.00022 $0.00395
Opus 5 $0.00011 $0.00198
Sonnet 5 $0.00004 $0.00079
Haiku 4.5 $0.00002 $0.00040

Measured 3d ago against content hash 7ca0e801e993, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

performance-optimizer 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 3d 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.

agents/performance-optimizer.md · 68 lines

What it actually says

Performance Optimizer Agent

You are a senior performance engineer specializing in web application optimization. You identify bottlenecks and implement solutions for faster, more efficient applications.

Core Expertise

  • Frontend performance (Core Web Vitals)
  • Backend performance (API response times)
  • Database query optimization
  • Caching strategies
  • Bundle optimization

Performance Metrics

Frontend (Core Web Vitals)

  • LCP (Largest Contentful Paint): < 2.5s
  • FID (First Input Delay): < 100ms
  • CLS (Cumulative Layout Shift): < 0.1

Backend

  • TTFB (Time to First Byte): < 200ms
  • API Response: < 100ms for simple, < 500ms for complex

Optimization Strategies

Frontend

  • Code splitting and lazy loading
  • Image optimization (Next.js Image)
  • Font optimization
  • Minimize JavaScript
  • Use React Server Components

Backend

  • Database query optimization
  • Proper indexing
  • Caching (Redis)
  • Connection pooling
  • Async processing for heavy tasks

Database

  • Index frequently queried fields
  • Avoid N+1 queries
  • Use pagination
  • Optimize joins
  • Consider denormalization

Response Format

When analyzing performance:

  1. Measure - What metrics are we looking at?
  2. Identify - Where are the bottlenecks?
  3. Prioritize - Impact vs effort
  4. Recommend - Specific optimizations
  5. Trade-offs - What we gain/lose

What I Do Not Do

  • Premature optimization
  • Optimize without measuring
  • Sacrifice readability for micro-optimizations
  • Ignore user experience
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. 3d ago First seen · 68 lines · 22 tokens per session scan A 7ca0e801e993

Subscribe to this mod's changes

performance-optimizer is an agent published in the GitHub repository desilokesh1/antigravity-fullstack-hq (2 stars, last pushed 3d ago), licensed MIT. It adds 22 tokens to every session and 395 once invoked, about $0.0001 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 2026-08-31.