Autonomous multi-agent system for e-commerce advertising. Features AI-driven creative generation, real-time multivariate testing, and cross-platform budget optimization (Meta, TikTok, Amazon). Uses historical performance data to autonomously refine targeting, bids, and creative assets, maximizing ROAS while reducing manual overhead. A scalable, data-driven solution for end-to-end campaign management.
Connect any MCP-compatible AI agent (Claude, Cursor, Copilot, Codex, Windsurf, Amp, Cline) to Penpot to create, audit, and maintain design systems — tokens, flows, interactions, animations, and design-to-code export to HTML/CSS/React.
Your product is great but the business never adds up and cash keeps leaking. Assemble the pieces into one money-making system: a value proposition that splits who pays from who uses, a revenue-model choice (subscription / usage / take-rate / ads / licensing), a cost structure, channels and relationships, and a consistency stress test that finds where the pieces fight and which assumption is most fatal — ending in a business model canvas and a clear narrative.
Audit AI agent workspaces for authority, secrets, data flow, memory, supply-chain, and evidence risks—locally and without executing target code.
Built for context-aware security review of MCP servers, AI agent skills, coding-agent plugins, and CLI extensions. It compares a repository's stated purpose with actual files, permissions, network calls, env var access, install scripts, and tool definitions, then returns an evidence-backed install-risk brief with severity, confidence, permission map, least-privilege notes, and a practical install decision.
This agent helps Python teams using the Anthropic or OpenAI SDK safely cut LLM spend without risking regressions. With zero code changes, it maps call sites and runs your test scenarios to rank token waste from missed prompt caching or heavy model tiers. It tests fixes in isolated git worktrees, enforcing a strict "do-no-harm" gate that reverts any patch failing to preserve behavior. It delivers a clear savings audit that converts into verified, behavior-preserving code patches upon opt-in.
This Skill is built on practical expertise in AI agent safety, prompt-injection defense, source-to-sink privacy review, tool and MCP metadata integrity, memory provenance checks, autonomous action scoping, and evidence-based verification. It helps agents separate instructions from evidence before tool calls, uploads, publishing, deletion, code execution, or network output.
A lightweight Copilot subscription agent runtime built on FastAPI and Copilot SDK. Manage multi-account OAuth, scheduled tasks, GitHub Enterprise support, and a bilingual Web UI.