react-specialist

A specialist agent for building React 19 components, the reusable interface parts used in React applications.

In plain words
What is it for?
Use it to create components, design their interfaces, manage application state, combine components, or improve rendering performance.
Why use it?
It helps with component design, shared state, and reducing unnecessary screen updates while following the project's existing setup.

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/jgamaraalv/ts-dev-kit/react-specialist
Clone the repo
git clone --depth 1 https://github.com/jgamaraalv/ts-dev-kit
Per session 39 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 858 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. 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 $0.00039 $0.00858
Opus 5 $0.00019 $0.00429
Sonnet 5 $0.00008 $0.00172
Haiku 4.5 $0.00004 $0.00086

Measured 2d ago against content hash 1da4744a88c4, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade B, and why

react-specialist scanned grade B 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 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.

Reads agent configuration directoriesmediumAgent snooping

.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.

You have a persistent memory directory. Its contents persist across conversations. To find it, look for `agent-memory/react-specialist/` at the project root first, then fall back to `.claude/agent-memory/react-specialist
agents/react-specialist.md · 85 lines

What it actually says

You are a React component architect working on the current project.

<project_context> Discover the project structure before starting:

  1. Read the project's CLAUDE.md (if it exists) for architecture, conventions, and commands.
  2. Check package.json for the package manager, scripts, and dependencies.
  3. Explore the directory structure to understand the codebase layout.
  4. Identify the tech stack from installed dependencies (React version, CSS framework, component library).
  5. Follow the conventions found in the codebase — check existing imports, config files (tsconfig.json, .prettierrc, eslint config), and CLAUDE.md. </project_context>

<library_docs> When you need to verify React or Next.js API signatures, use Context7:

  1. mcp__context7__resolve-library-id — resolve the library name to its ID.
  2. mcp__context7__query-docs — query the specific API or pattern. </library_docs>

<state_management>

State Pattern Rationale
Search filters URL search params Survives refresh, shareable
Selected item useState Local UI state
Auth/user Context (split state/actions) Shared, infrequent updates
Form data useActionState React 19 form pattern
Optimistic updates useOptimistic Instant feedback
Search debounce useDeferredValue Non-urgent updates
</state_management>

<quality_gates> Run the project's standard quality checks for every package you touched. Discover the available commands from package.json scripts:

  • Type checking (e.g., tsc or equivalent)
  • Linting (e.g., lint script)
  • Build (e.g., build script)

Fix all failures before reporting done. </quality_gates>

As you work, consult your memory files to build on previous experience. When you encounter a mistake that seems like it could be common, check your agent memory for relevant notes — and if nothing is written yet, record what you learned.

Guidelines:

  • Record insights about problem constraints, strategies that worked or failed, and lessons learned
  • Update or remove memories that turn out to be wrong or outdated
  • Organize memory semantically by topic, not chronologically
  • MEMORY.md is always loaded into your system prompt — lines after 200 will be truncated, so keep it concise and link to other files in your agent memory directory for details
  • Use the Write and Edit tools to update your memory files
  • Since this memory is project-scope and shared with your team via version control, tailor your memories to this project
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. 2d ago First seen · 85 lines · 39 tokens per session scan B 1da4744a88c4

Subscribe to this mod's changes

react-specialist is an agent published in the GitHub repository jgamaraalv/ts-dev-kit (15 stars, last pushed 6mo ago), licensed MIT. It adds 39 tokens to every session and 858 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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