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 skills add DDS-Solutions/AI-TadPole-OS --skill nextjs-react-expertgit clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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/dds-solutions/ai-tadpole-os/nextjs-react-expert)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/nextjs-react-expert"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/nextjs-react-expert/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/dds-solutions/ai-tadpole-os/nextjs-react-expert"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/nextjs-react-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00037 | $0.01683 |
| Opus 5.5 | $0.00015 | $0.00673 |
| Sonnet 5.5 | $0.00007 | $0.00337 |
| Haiku 4.5 | $0.00004 | $0.00168 |
Grade A, and why
nextjs-react-expert 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / nextjs-react-expert
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Sequential fetch waterfalls, bloated vendor bundles, or unmemoized re-render cascades.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
React & Next.js Performance Optimization Core
Philosophy: Eliminate waterfalls first, optimize bundle payload second, eliminate re-render jank third.
Native Target: In Tadpole OS, the frontend is a Vite + React 19 SPA inside a Tauri desktop shell. SSR rules apply when building external apps; SPA & Tauri IPC rules apply for core OS.
Workflow Bindings: Integrated into/refactorand/ui-ux-pro-max.
🎯 Progressive Disclosure & L3 Reference Index
Read the core Sovereign priorities below; consult deep L3 Reference Guides on demand:
| L3 Reference Guide | Impact / Priority | Trigger / When to Load |
|---|---|---|
references/1-async-eliminating-waterfalls.md |
🔴 CRITICAL | Slow page loads, sequential await fetch waterfalls |
references/2-bundle-bundle-size-optimization.md |
🔴 CRITICAL | Large JS bundles (>200KB), barrel import bloat, dynamic imports |
references/3-server-server-side-performance.md |
🟠 HIGH | Slow Server-Side Rendering (SSR), streaming Suspense boundaries |
references/4-client-client-side-data-fetching.md |
🟡 MEDIUM-HIGH | Client-side SWR/TanStack query deduplication, optimistic updates |
references/5-rerender-re-render-optimization.md |
🟡 MEDIUM | Excessive React re-renders, Zustand selector tuning, React.memo |
references/6-rendering-rendering-performance.md |
🟡 MEDIUM | Virtualization (@tanstack/react-virtual), layout thrashing |
references/7-js-javascript-performance.md |
⚪ POLISH | Fast loops, memoized expensive compute, micro-benchmarks |
references/8-advanced-advanced-patterns.md |
🔵 ADVANCED | useLatest, init-once refs, custom hook abstractions |
references/9-cache-components.md |
🔴 CRITICAL (Next 16+) | use cache, cacheLife, Partial Prerendering (PPR), cacheTag |
scripts/react_performance_checker.py |
🛠️ AUDITOR | Automated waterfall, barrel-import, and memoization scanner |
What ships with it
11 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.
- references/1-async-eliminating-waterfalls.md 9.0 KB
- references/2-bundle-bundle-size-optimization.md 6.5 KB
- references/3-server-server-side-performance.md 13 KB
- references/4-client-client-side-data-fetching.md 7.0 KB
- references/5-rerender-re-render-optimization.md 16 KB
- references/6-rendering-rendering-performance.md 10 KB
- references/7-js-javascript-performance.md 17 KB
- references/8-advanced-advanced-patterns.md 3.9 KB
- references/9-cache-components.md 3.1 KB
- scripts/convert_rules.py 7.0 KB runs code
- scripts/react_performance_checker.py 10.0 KB runs code
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.
- 12d ago Changed · +28 lines · -11 tokens per session d4645a6747d3
- 1mo ago First seen · 57 lines · 48 tokens per session scan A 80c957aa8d51
nextjs-react-expert is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 1,683 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
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