By tonone-ai
Audit power management in embedded and IoT firmware by analyzing sleep modes, wake sources, power state machines, radio duty cycles, and battery life estimates to diagnose battery drain and optimize power budgets.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub tonone-ai/tonone --plugin volt-powerEmbedded & IoT engineer — firmware, microcontrollers, edge computing, device protocols
Embedded development agents providing expertise in RTOS, firmware, and IoT
Turn on Godmode for Claude Code. 126 skills. 7 subagents. Zero configuration.
Use this agent for comprehensive performance testing, profiling, and optimization recommendations. This agent specializes in measuring speed, identifying bottlenecks, and providing actionable optimization strategies for applications. Examples:\n\n<example>\nContext: Application speed testing
Ultra-compressed communication mode. Cuts 65% of output tokens (measured) while keeping full technical accuracy by speaking like a caveman.
Frontend design skill for UI/UX implementation
Design and build networking infrastructure — VPCs, subnets, DNS, load balancers, firewall rules. Use when asked to "set up networking", "VPC design", "configure DNS", "load balancer setup", "network architecture", or "firewall rules".
Generate onboarding documentation — what this project does, how to set up locally, where things live, key decisions, how to deploy. Written for day-one engineers who know nothing. Use when asked for "onboarding docs", "new engineer guide", "how to get started", or "developer setup".
Implement a reusable, accessible, typed component from a design spec. Use when asked to "create a component", "build a widget", "implement this design", or "reusable UI element".
Verify observability posture — audit monitoring coverage, find blind spots, prioritize gaps. Use when asked "is monitoring sufficient", "observability review", "are we covered", or "pre-launch monitoring check".
ML reconnaissance — inventory all models, pipelines, data sources, and monitoring. Use when asked "what ML do we have", "model inventory", or "ML assessment".