Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/textura-agency/next16-claude-starternpx agentmods add skills/textura-agency/next16-claude-starter/optimize-loadWrote 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/textura-agency/next16-claude-starter/optimize-load)<a href="https://agentmods.dev/skills/textura-agency/next16-claude-starter/optimize-load"><img src="https://agentmods.dev/badge/skills/textura-agency/next16-claude-starter/optimize-load/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/textura-agency/next16-claude-starter/optimize-load"><img src="https://agentmods.dev/badge/skills/textura-agency/next16-claude-starter/optimize-load.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00194 | $0.05036 |
| Opus 5.5 | $0.00078 | $0.02014 |
| Sonnet 5.5 | $0.00039 | $0.01007 |
| Haiku 4.5 | $0.00019 | $0.00504 |
Grade A, and why
optimize-load 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 11d 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.
`origin-sync.ts` after hydration. Fetch the deployed `og:image` and curl it: How it starts
The opening of the file, as written. The whole thing — 314 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Get the page into the green
Lighthouse, two form factors (plus tablet when it matters), four categories,
two audiences (people and the robot form), then fix and prove it. Rewritten from
optimisation passes on ~50 production sites built from this starter; each lever
says whether it is a rule (held on ≥ 3 sites) or observed (1–2).
Before fixing, read obsidian/knowledge/fix-catalog.md and
obsidian/knowledge/pitfalls.md.
The bar (reached on every one of those sites): Performance ≥ 90 on mobile and desktop; Accessibility, Best Practices and SEO = 100 on both, for people and for the robot form. 100 on the last three is reachable without changing the design — the classic "axe caught a fade mid-way" flake is fixable (§3). Don't chase Performance from 96 to 100; do chase an A11y 96.
Scope. This skill owns the load: navigation to settled. Scroll jank after load is
optimize-performance— Lighthouse never scrolls. A WebGL scene: runoptimize-3d-scenefirst. Real-phone behaviour Lighthouse can't see (iOS toolbar, 120 Hz, menus):mobile-device-qa.
The loop
Build → audit (people + robot, mobile + desktop) → attribute → fix one thing → re-audit. Never report a score you did not re-measure.
0. Rules of measurement
Ignoring these produces confident wrong answers. Each one cost real time.
- Audit the build, never
next dev.yarn build && yarn start. Kill the old server by port first (next startruns asnext-server), and start the new one only if the build succeeded — a failed build serves the previous.next, and the A/B compares the old build with itself. - Median of ≥ 3 runs; 5 before calling a regression. On one unchanged build
LCP swung 2.7 → 4.6 s and CLS 0 → 0.18. Lantern can simulate the same
preloader-gated LCP at 0.85 s or 4.6 s run to run (one live site scored 89 /
90 / 68 / 90 / 68 in one sitting) — compare
metrics → observedLargestContentfulPainttoo. - People and robot are different pages. The starter's proxy serves bots —
and Lighthouse's default UA, and PageSpeed Insights — the robot form
(
references/robot-path.md). A people run needs a plain Chrome UA. Audit both; the robot form is what Google and PSI score. - Localhost is a floor, not the record. One site's mobile LCP was 4.8 s
locally and 31 s on its real host (11 MB of raw PNGs Lantern only charged
on a real network). The other way round too: on asset-heavy pages localhost
over HTTP/1.1 bills ~4–6 extra LCP points. Judge local A/Bs by deltas and TBT;
take the record on the deployed URL (
--url https://…). - A shared or busy machine moves TBT 2×. Interleave A/B arms (old, new,
old, new) so both see the same load; note
sysctl -n vm.loadavg. Build the baseline from agit worktreeof the base branch, never by copying.next/. - Change one thing at a time, and test the hypothesis first. The opening loader was the obvious suspect for a 4 s LCP; removing it entirely moved TBT 20 ms and made two profiles worse.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago Changed · +165 lines · +24 tokens per session 09d4a2f3e8ea
- 29d ago First seen · 149 lines · 170 tokens per session scan A 455e3b39b68e
optimize-load is a skill published in the GitHub repository textura-agency/next16-claude-starter (137 stars, last pushed 3d ago), licensed Unlicense. It adds 194 tokens to every session and 5,036 once invoked, about $0.0008 per session on Opus 5.5. 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 2026-09-19.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…