By tonone-ai
Design safety guardrails for AI systems: classify inputs, validate outputs, detect PII, and enforce policy rules to prevent misuse.
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npx claudepluginhub tonone-ai/tonone --plugin guard-designDesign eval harnesses — task schemas, metrics, dataset versioning, eval-as-code patterns.
Write a hardening playbook — CIS benchmark mapping and implementation steps
Design an evaluation framework for a ML model
Build a forecasting model for a time series
Map product data flows and identify regulatory triggers
AI Operations Team — Guard: Input/output safety filters, PII detection, content moderation, and AI policy enforcement at runtime.
Engineering process for solo founders and teams up to 50 engineers. Agents do architecture, code review, QA, and security. You make two decisions per feature.
Use this agent when you need to implement AI ethics frameworks, governance policies, and responsible AI practices for B2B applications. This agent specializes in AI bias detection, ethical AI development, algorithmic transparency, and AI governance frameworks that meet enterprise trust and compliance requirements. Examples:
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