Features
Mentor-like feedback for AI agents
Interrupts pattern inertia before wrong paths
Reduces over-engineering in agent workflows
Improves success rate by 27% (per study)
Halves harmful agent actions (per study)
Built on Anthropic's Model Context Protocol
Open source with 70k+ downloads
Listed in Anthropic's official MCP repo
PulseMCP most popular (Oct 2025)
Plug and play integration with MCP agents
KISS principle enforcement for agents
Supports coding, ambiguous, and high-risk tasks
mngr: run any coding agent in parallel anywhere
Bouncer: filter and heal your Twitter feed
Sculptor: manage parallel coding agents with UI
Blueprint: one-shot larger coding tasks
Vet: prevent AI coding agent mistakes
Latchkey: fine-grained HTTP permissions for agents
Ratchets: Rust tool for flexible style violation budgets
Open-source tools and community
Research publications on deep learning and ARC-AGI
Policy work for human-centric AI
Agent behavior auditing and control
Parallel agent orchestration across environments
