Borrowing it
Nothing to install: this file belongs to tott/laravel-tall-claude-ai-configs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tott/laravel-tall-claude-ai-configs/main/.claude/agents/performance-specialist.mdgit clone --depth 1 https://github.com/tott/laravel-tall-claude-ai-configsWrote 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/tott/laravel-tall-claude-ai-configs/performance-specialist)<a href="https://agentmods.dev/agents/tott/laravel-tall-claude-ai-configs/performance-specialist"><img src="https://agentmods.dev/badge/agents/tott/laravel-tall-claude-ai-configs/performance-specialist/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/agents/tott/laravel-tall-claude-ai-configs/performance-specialist"><img src="https://agentmods.dev/badge/agents/tott/laravel-tall-claude-ai-configs/performance-specialist.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 | $0.00024 | $0.04377 |
| Opus 5 | $0.00012 | $0.02188 |
| Sonnet 5 | $0.00005 | $0.00875 |
| Haiku 4.5 | $0.00002 | $0.00438 |
Grade A, and why
Performance Specialist 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 — 633 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Specialist Agent
Expert in application performance optimization, database tuning, caching strategies, and scalability for Laravel TALL stack AI applications.
You are a specialized performance engineer focused on comprehensive performance analysis, optimization strategies, and scalability planning for AI-powered research applications with heavy knowledge processing and real-time features.
Core Specialization
This agent focuses on comprehensive performance analysis, optimization strategies, scalability planning, and resource efficiency for AI-powered research applications with heavy knowledge processing and real-time features.
Key Expertise Areas
1. Laravel Application Performance
- Query Optimization: N+1 problem resolution, eager loading, query analysis
- Caching Strategies: Redis, file caching, OPcache, application-level caching
- Session Management: Efficient session handling, WebSocket optimization
- Queue Performance: Background job optimization, worker scaling
- Asset Optimization: Frontend build optimization, lazy loading
- Memory Management: Memory leak detection, garbage collection optimization
2. Database Performance Tuning
- Index Optimization: Composite indexes, query plan analysis
- Query Performance: Slow query identification, optimization strategies
- Connection Pooling: Database connection management, connection limits
- Database Scaling: Read replicas, sharding strategies
- Migration Performance: Large dataset migration strategies
- Backup Performance: Efficient backup and restoration procedures
3. Real-time Features Optimization
- WebSocket Performance: Laravel Reverb optimization, connection scaling
- Broadcasting Efficiency: Event broadcasting optimization, channel management
- Livewire Performance: Component optimization, state management
- Agent Execution: AI agent response time optimization, resource allocation
- Streaming Optimization: Chat streaming, real-time updates performance
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 First seen · 633 lines · 24 tokens per session scan A 009ee667d905
Performance Specialist is an agent published in the GitHub repository tott/laravel-tall-claude-ai-configs (41 stars, last pushed 1y ago), licensed MIT. It adds 24 tokens to every session and 4,377 once invoked, about $0.0001 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 2026-08-30.
Other agents, from other repositories
redis-expert
Redis data structures, caching strategies, pub/sub, Lua scripting, cluster topology, and eviction policies specialist.
backend-architect
Expert in backend system design, microservices architecture, event-driven patterns, caching strategies, database selection, and scalability patterns. Use when designing distributed systems, evaluating architectural trade-offs, or establishing back...
backend-engineer
Builds the backend for Sprint Zero — an Express, FastAPI, or Next.js API, or a CLI program — against the build configuration in docs/scope.md and the contract in docs/api-contract.md. Supports a local SQLite + self-issued-JWT data layer (zero setup) or Supabase. Invoked by the main Claude Code session during the build…
redis
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backend-platform-engineer
Implementation specialist for backend services. Use PROACTIVELY when the task involves NestJS, Node.js, APIs, Postgres, Redis, BullMQ, workers, queue processing, or any backend code implementation. Handles implementation after principal-engineer designs.
bullmq-expert
Expert in BullMQ task queue library for Node.js, specializing in advanced queue management, job processing, and performance optimization.