mindmap, mcp server, artifact

Artifact layer for agent-human representations. One API call, one SVG. Zero dependencies, renders in any markdown.

Evidence-based learning engine — first-principles curricula, free-recall verification with receipts, FSRS-scheduled memory, and explorable artifacts. Learn anything; keep it.

LLM-compiled knowledge bases for any AI agent. Parallel multi-agent research, thesis-driven investigation, source ingestion, wiki compilation, querying, and artifact generation.

Native, local-first knowledge graph engine for code and project artifacts—inspired by Graphify, built in Rust, and evolving beyond it.

Vlad's Playbook — a 48-chapter operator field manual where every artifact is live, clickable, and forwardable. 31 interactive widgets, a self-updating AI radar, hand-verified model leaderboards, embedded case studies — and the repo runs the agent workflow the book teaches.

Automatically create new skills based on past agent traces

900+ pure-markdown skills for autonomous AI research, organized as 9 freely-composable packages over a 4-layer hierarchy (Campaign → Strategy → Tactic → SOP). Non-linear orchestration with backtracking, 6 MCP integrations. The AI is the researcher — you set the direction.