70+ specialized AI agents across 11 categories, each with deep domain knowledge, framework-specific expertise, and intelligent fallback chains. From TypeScript React to Rust Axum, from Playwright E2E to Kubernetes deployments.
70+ AGENTS
GENOME
FILTER
code-ts
TypeScript / Fastify
code-react
React / Next.js
test-vitest
Vitest / TDD
test-playwright
E2E / Playwright
security-owasp
OWASP / SAST
reviewer-ts
Code Quality
ops-docker
Containers
architect
DAG / Planning
8 of 70+ matched · 62 filtered out
TypeScript (core, React, Next.js, Fastify, Node.js, Vue, Angular), Python (Django, FastAPI, Flask, Celery), Go (core, Gin, gRPC), Rust (core, Axum, Tokio), Java (Spring Boot, Quarkus), Kotlin (Android, Ktor), Swift (iOS), and a polyglot generalist. Deep framework knowledge in each.
Vitest, Jest, Playwright, Cypress, pytest, unittest, Go table-driven, Rust cargo test, JUnit 5, Spring Boot Test, XCTest, Android instrumented tests, plus test-runner agents per language (Python, JS, Rust, Go, Java) that execute and validate tests.
Multi-lens code review (correctness, style, performance, security, naming), accessibility auditing (WCAG 2.1), performance review, integration checks, and quality assurance.
OWASP Top 10 scanning, API authentication auditing, dependency vulnerability scanning, and general SAST with CWE-referenced findings.
Docker optimization, Kubernetes manifests, Terraform modules, CI/CD pipelines (GitHub Actions, GitLab CI), and general infrastructure investigation.
AI product owner for requirement enrichment, task architect for DAG decomposition with expert assignment, and project-inception intake for new-project onboarding conversations.
System design with ADRs, REST/GraphQL API architecture, and frontend architecture with component design and state management strategy.
SQL optimization with EXPLAIN ANALYZE, zero-downtime migrations (expand-contract), schema design with ER modeling, and general data engineering.
Frontend (Core Web Vitals, bundle optimization), backend (API latency, N+1 detection), database (query plans, indexing), and full-stack performance analysis.
Technical writing, API documentation with OpenAPI specs, and architecture documentation with Mermaid diagrams and ADRs.
Linting setup (ESLint, ruff, clippy), build tooling (Vite, turbo, pnpm), project onboarding with CLAUDE.md generation, and general DX improvement.
SWE-bench Verified runner — applies candidate patches to target repos and runs the official Princeton Docker eval harness for pass/fail scoring.
Every team has unique workflows. Create custom expert agents that understand your specific needs.
Define your own expert agent types with custom system prompts, models, and tools.
Connect any service via the open adapter interface.
Build multi-step job pipelines tailored to your team's process.
Per-project constraints that enforce your standards.
When a job comes in, the platform automatically classifies it and routes mini-jobs to the right expert agents. Simple work gets fast, cost-effective models. Complex reasoning gets powerful models. You can override any routing decision.
Request access to see how expert agents handle real engineering jobs.
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