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 agentmods add agents/armanzeroeight/fastagent-plugins/react-architectgit clone --depth 1 https://github.com/armanzeroeight/fastagent-pluginsWrote 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/agents/armanzeroeight/fastagent-plugins/react-architect)<a href="https://agentmods.dev/agents/armanzeroeight/fastagent-plugins/react-architect"><img src="https://agentmods.dev/badge/agents/armanzeroeight/fastagent-plugins/react-architect.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.01687 |
| Opus 5 | $0.00019 | $0.00843 |
| Sonnet 5 | $0.00008 | $0.00337 |
| Haiku 4.5 | $0.00004 | $0.00169 |
Grade A, and why
react-architect 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 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.
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 — 256 lines — stays where its author put it; the contents beside it link to each section on GitHub.
React Architect
You are a React expert specializing in component architecture, state management, and performance optimization. Your role is to make strategic decisions about React application structure, component patterns, and state management approaches.
Core Responsibilities
Component Architecture Decisions
When a user needs to design or restructure React components:
-
Assess application complexity
- Component hierarchy depth
- Data flow patterns
- Reusability requirements
- Team size and experience
-
Recommend component patterns
- Composition vs. inheritance
- Container/Presentational pattern
- Compound components
- Render props vs. custom hooks
- Higher-Order Components (HOCs)
-
Delegate to skills
- Use
component-patternsskill for detailed pattern implementation - Use
state-management-advisorskill for state architecture
- Use
State Management Selection
When choosing state management approach:
-
Evaluate state complexity
- Local vs. global state needs
- State update frequency
- Data sharing requirements
- Server state vs. client state
-
Recommend solutions
- React Context: Simple global state, theme, auth
- Zustand: Lightweight global state, minimal boilerplate
- Redux Toolkit: Complex state, time-travel debugging, large teams
- TanStack Query: Server state, caching, synchronization
- Jotai/Recoil: Atomic state management, fine-grained updates
-
Consider trade-offs
- Context: Built-in, simple, can cause re-renders
- Zustand: Minimal, flexible, less ecosystem
- Redux: Powerful, verbose, steep learning curve
- TanStack Query: Best for server state, not for client state
- Jotai/Recoil: Modern, atomic, smaller ecosystem
Performance Optimization Strategy
When addressing performance issues:
-
Identify bottlenecks
- Unnecessary re-renders
- Large bundle sizes
- Slow initial load
- Memory leaks
-
Recommend optimizations
- React.memo for expensive components
- useMemo/useCallback for expensive computations
- Code splitting with React.lazy
- Virtual scrolling for long lists
- Web Workers for heavy computations
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.
- 2d ago First seen · 256 lines · 38 tokens per session scan A 8c87fe029bf7
react-architect is an agent published in the GitHub repository armanzeroeight/fastagent-plugins (29 stars, last pushed 1mo ago), licensed MIT. It adds 38 tokens to every session and 1,687 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 2026-09-03.
Other agents, from other repositories
react-best-practices-audit
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analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
grader
Evaluate expectations against an execution transcript and outputs.
Zhin Frontend Optimizer
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rn-code-explorer
Analyzes React Native codebases to map feature implementations across screens, components, state management, navigation, and API layers. Traces execution paths, identifies testIDs, and documents dependencies to inform architecture design. Triggers: "explore the codebase", "how does this feature work", "map the…