By tonone-ai
Head of Product — product strategy, requirements, and engineering handoff via the Helm↔Apex interface
Product landscape reconnaissance — survey existing briefs, research, strategy, and team output before writing new briefs or dispatching specialists. Use when asked to "understand the product state", "what briefs exist", "what has the team produced", "orient me on this product", or before starting a new product initiative.
Scope arbitration — resolve disagreements between product and engineering on what is in or out of scope, with a decision log and escalation path. Use when asked to "resolve this scope disagreement", "arbitrate between product and eng", "scope is creeping", "we can't agree on what's in scope", or "help us decide what to cut".
Use when asked to write a product brief, turn a feature idea into a spec, define requirements for something to build, or clarify what a product should do and why. Examples: "write a brief for X", "turn this idea into a spec", "what should we build here", "help me define requirements".
Use when a product brief is finalized and ready to hand off to the engineering team, or when asked to send a brief to Apex, kick off engineering work, or start development on a product spec. Examples: "hand this off to engineering", "send brief to Apex", "start building this", "kick off dev on this spec".
Use when asked to build a product roadmap, prioritize a backlog, decide what to build next, or sequence a list of feature ideas. Examples: "what should we build next", "prioritize this backlog", "make a roadmap", "RICE score these features".
Uses power tools
Uses Bash, Write, or Edit tools
Own this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimOwn this plugin?
Verify ownership to unlock analytics, metadata editing, and a verified badge. GitHub access is read-only (username + org membership).
Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
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 helmEngineering + 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
Product team — 8 agents: Helm, Echo, Lumen, Draft, Form, Crest, Pitch, Surge
Agent-first PM toolkit with 9 specialist agents and 18 skills for solo developers and small teams
12 PM-specific agent skills, 6 workflow commands, 3 automation hooks for Product Managers
Dynamic task-based agentic delegation with builder/validator pairs and meta-prompt team orchestration
Product Discovery workflow automation for PM teams — 9 phases from problem framing to go/no-go decision, 12 sub-agents
Ultra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.