Data quality and pipeline health check — freshness, schema drift, null rates, orphaned records, pipeline status. Use when asked about "data quality check", "pipeline health", "is our data fresh", or "schema drift".
Build zero-downtime database migrations — forward SQL, rollback SQL, deployment sequence. Use when asked to "write migration", "schema change", "add column", "rename table", "drop column", or "migrate safely".
Build a data pipeline — ETL/ELT with extraction, transformation, loading, error handling, and scheduling. Use when asked to "build ETL", "data pipeline", "move data from X to Y", or "sync data".
Optimize slow database queries — analyze execution plans, add indexes, rewrite queries. Use when asked about "slow query", "optimize SQL", "query performance", or "explain this query".
Database reconnaissance — full inventory of schema, migrations, data volume, backups, connection pooling, and query patterns. Use when asked to "assess this database", "understand the schema", or "database health check".
Uses power tools
Uses Bash, Write, or Edit tools
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Engineering + product, second to none.
Your elite AI team as Claude Code agents. 2 leads + 21 specialists. 125 skills. Every major engineering and product discipline covered.
Simple by default. Scalable by design.
Right now, everyone gets a generalized AI assistant. Engineers, product managers, designers, strategists — all prompting separately, getting separate outputs, then copying results into Slack threads for the next person to feed back into AI. It's a relay race where every handoff loses context.
That's the wrong unit of automation. Instead of giving each person an AI assistant, give the whole company an AI team. Specialists that talk to each other, share context, and run the show end to end — from user research to infrastructure to deployment — without the copy-paste relay.
That's Tonone. Not twenty-three copies of the same generalist. Twenty-three specialists, each owning one domain, coordinated by leads who know when to call who and at what depth.
Complexity is debt. Every unnecessary abstraction, every over-engineered solution, every "just in case" feature — it all accrues interest. It slows you down today and buries you tomorrow.
Scalability compounds. When you build simple, correct foundations, they carry more weight over time without breaking. Simple systems are easier to debug, easier to extend, and easier to hand off.
No boilerplate generators. No tutorial-grade scaffolds. Production-ready output that respects your codebase, your stack, and your time.
| Agent | Hat | What They Do |
|---|---|---|
| Apex | Engineering Lead | Orchestrates the team, scopes work, controls depth and budget |
| Forge | Infrastructure | Cloud services, networking, IaC, cost optimization |
| Relay | DevOps | CI/CD, deployments, GitOps, developer experience |
| Spine | Backend | APIs, system design, performance, distributed systems |
| Flux | Data | Databases, migrations, pipelines, data modeling |
| Warden | Security | IAM, secrets, compliance, threat modeling |
| Vigil | Observability + Reliability | Monitoring, alerting, SRE, incident response, SLOs |
| Prism | Frontend/DX | UI, internal tools, developer portals |
| Cortex | ML/AI | Model training, MLOps, feature engineering, LLM integration |
| Touch | Mobile | Native iOS/Android, cross-platform, app stores |
| Volt | Embedded/IoT | Firmware, microcontrollers, edge computing, protocols |
| Atlas | Knowledge Engineering | Architecture docs, ADRs, API specs, system diagrams |
| Lens | Data Analytics & BI | Dashboards, metrics design, reporting, data storytelling |
| Proof | QA & Testing | Test strategy, E2E suites, integration testing, flaky triage |
| Pave | Platform Engineering | Developer experience, golden paths, service catalogs |
| Agent | Hat | What They Do |
|---|---|---|
| Helm | Head of Product | Orchestrates the product team, writes briefs, hands off to Apex |
| Echo | User Research | User interviews, personas, Jobs-to-Be-Done, feedback synthesis |
| Lumen | Product Analytics | Metrics frameworks, funnel analysis, OKRs, A/B test design |
| Draft | UX Design | User flows, information architecture, wireframes |
| Form | Visual Design | Brand identity, color systems, typography, design system |
| Crest | Product Strategy | Roadmap planning, prioritization, competitive analysis |
| Pitch | Product Marketing | Positioning, messaging, value prop, GTM, launch copy |
| Surge | Growth | Acquisition channels, activation funnels, retention playbooks |
Prerequisites: Claude Code v1.0+
/plugin marketplace add tonone-ai/tonone
/plugin install tonone@tonone-ai
Then just talk to them:
npx claudepluginhub tonone-ai/tonone --plugin fluxEngineering + Product + Operations + Legal + Design + Data Science + Security Operations + Developer Experience + Infrastructure Specialist + AI Operations team — 100 agents as Claude Code specialists. Infrastructure, DevOps, backend, security, ML/AI, mobile, UX, analytics, growth, revenue, content, PR, customer success, finance, people, operations, support, contracts, compliance, IP, governance, regulatory, color systems, typography, motion, accessibility, design tokens, forecasting, feature engineering, model training, drift monitoring, vector search, LLM fine-tuning, pen testing, detection engineering, incident response, zero trust, API docs, SDK design, developer onboarding, Kubernetes, Terraform, FinOps, service mesh, edge computing, caching, queuing, multi-cloud, chaos engineering, model deployment, LLM evaluation, AI observability, guardrails, prompt engineering, embeddings, ranking, and more.
UX designer — user flows, information architecture, wireframes, and interaction design
Backend engineer — APIs, system design, performance, distributed systems
Platform engineer — developer experience, service catalogs, internal CLIs, golden paths, environment management
Growth engineer — acquisition channels, activation funnels, retention playbooks, and PLG strategy
Engineering team — 15 agents: Apex, Forge, Relay, Spine, Flux, Warden, Vigil, Prism, Cortex, Touch, Volt, Atlas, Lens, Proof, Pave
Schema design, query optimization, migrations, indexing, transactions, data integrity, and connection pooling.
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