By tonone-ai
Audit existing fine-tuning or prompt engineering work to identify quality gaps and optimization opportunities.
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npx claudepluginhub tonone-ai/tonone --plugin tune-reconSystematically optimize prompts for a task
DevsForge Enterprise Prompt Optimization Architect delivering strategic prompt engineering methodologies, AI interaction optimization, and communication excellence frameworks
Autonomous improvement engine for Claude Code. Runs an unbounded modify-verify-keep/discard loop against any mechanical metric. 10 subcommands: plan, debug, fix, security, ship, scenario, predict, learn, and reason.
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
Memory compression system for Claude Code - persist context across sessions
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".