optimize

optimize is a skill for Claude Code, Codex from T4LEL/Claude-Arsenal. It costs 40 tokens per session (856 once invoked), scanned A, original, MIT.

A measurement-led process for making an application faster, lighter, or cheaper to run. It measures likely bottlenecks, changes one at a time, and checks the results afterward.

In plain words
What is it for?
Use it to investigate page speed, bundle size, database queries, GPU or hosting costs, and other measured performance issues.
Why use it?
It avoids guessing at performance problems and helps show whether a change actually improved the application.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions CLAUDE.md.

Good fit Use it to investigate page speed, bundle size, database queries, GPU or hosting costs, and other measured performance issues.

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Install with agentmods
npx agentmods add skills/t4lel/claude-arsenal/optimize
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.

Any agent
npx skills add T4LEL/Claude-Arsenal --skill optimize
Clone the repo
git clone --depth 1 https://github.com/T4LEL/Claude-Arsenal

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for optimize

README.md
[![agentmods](https://agentmods.dev/badge/skills/t4lel/claude-arsenal/optimize.svg)](https://agentmods.dev/skills/t4lel/claude-arsenal/optimize)
Your own site
<a href="https://agentmods.dev/skills/t4lel/claude-arsenal/optimize"><img src="https://agentmods.dev/badge/skills/t4lel/claude-arsenal/optimize.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 856 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00040 $0.00856
Opus 5 $0.00020 $0.00428
Sonnet 5 $0.00008 $0.00171
Haiku 4.5 $0.00004 $0.00086

Measured 7d ago against content hash ecc7827d287e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

optimize 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 7d 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.

skills/optimize/SKILL.md · 58 lines

How it starts

The opening of the file, as written. The whole thing — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Optimize

Fast and cheap, with proof — measurement is the entry fee: no measurements, no changes.

Copy this checklist and check off items as you complete them:

Optimize Progress:
- [ ] Step 1: Measure — real numbers across the stack
- [ ] Step 2: Rank — top 1-3 bottlenecks by impact
- [ ] Step 3: Fix — one bottleneck at a time
- [ ] Step 4: Re-measure — before/after pasted, revert if no gain
- [ ] Step 5: Lock in — perf budget recorded in CLAUDE.md

Step 1 — Measure (paste real output, no exceptions)

Run every measurement that applies:

  • Lighthouse / Web Vitals on the key pages — home, the page the user called slow, the critical conversion path.
  • next build output for bundle size and per-route weight (or the equivalent build analyzer for the stack).
  • EXPLAIN ANALYZE on any suspect query.
  • Supabase MCP get_advisors for index and RLS-performance findings.
  • The platform cost dashboard (Vercel usage, Supabase billing) for the actual dollar line items.

Numbers recalled from memory or a past session are unverified assumptions — label them that way and re-measure before acting on them. If nothing here can actually be run — no build, no query plan, no dashboard access — stop and report exactly what instrumentation is missing instead of guessing at fixes.

Step 2 — Rank

List the bottlenecks found in Step 1 by user impact (what visitors feel) and cost impact (what shows up on the bill). Pick the top 1-3 only. Fixing bottleneck #7 while #1 still stands is wasted work.

Step 3 — Fix

Delegate to the performance-engineer agent with one bottleneck at a time and the measurement that flagged it. Boring wins first: image formats/sizes, HTTP/data caching, N+1 queries, missing indexes, bundle splitting. Reach for anything exotic only after the boring list is exhausted. If the fix touches a library's caching or data-fetching API — Next.js, the Supabase client, anything version-sensitive — pull current usage via the context7 MCP tools first; these APIs shift across versions and a stale pattern is how "optimizations" quietly regress. Secrets stay in env vars and are never printed into chat, code, logs, or commits — a fix that needs a key belongs in an env var, not inline.

Read the full file on GitHub · 58 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. 7d ago First seen · 58 lines · 40 tokens per session scan A ecc7827d287e

Subscribe to this mod's changes

optimize is a skill published in the GitHub repository T4LEL/Claude-Arsenal (1 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 856 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 2026-08-31.

Related

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