23blocks OS
Official@23blocks-os · Boulder, CO
Backend as a Service + AI Agent Infrastructure. 15+ production-ready API blocks. Open-source AI orchestration with AI Maestro.
Agent Skills by 23blocks OS
Showing 10 vetted skills indexed across 2 GitHub repositories.
23blocks-OSplanning
Manage complex tasks by creating and updating persistent markdown planning files.
23blocks-OSai-maestro-agents-management
Manage AI agent lifecycles and configurations through a command-line interface.
23blocks-OSgraph-query
Query a code graph database to analyze dependencies and change impact.
23blocks-OSmemory-search
Search conversation history using hybrid, semantic, or term-based modes.
23blocks-OSdocs-search
Search project documentation for function signatures and API details before implementing code.
23blocks-OSagent-messaging
Send and receive signed messages between AI agents using AMP.
23blocks-OSAI Maestro Code Graph Query
Queries code graph to determine component relationships and change impact.
23blocks-OSAI Maestro Memory Search
Retrieve prior discussions and decisions via memory-search.sh before starting new tasks.
23blocks-OSAI Maestro Agent Messaging
Send and receive messages between AI Maestro agents via CLI scripts.
23blocks-OSAI Maestro Documentation Search
Search project documentation for function signatures and API details before coding.
Frequently Asked Questions About 23blocks OS
FAQPage SchemaWhat specific technical tasks does 23blocks OS enable?▼
23blocks OS enables precise code graph dependency analysis, semantic retrieval of historical project decisions, and structured documentation lookups. It facilitates inter-process communication through signed messaging protocols and maintains persistent project state via markdown-based planning files, ensuring consistency across complex development cycles.
Which personas benefit most from these technical capabilities?▼
Software engineers, backend architects, and technical leads managing large, distributed codebases benefit most. These capabilities are designed for developers who require deep visibility into component relationships, historical context for architectural decisions, and robust communication channels between modular system components.
What are the prerequisites for implementing these capabilities?▼
Implementation requires a codebase structured for graph-based dependency analysis and the presence of indexed project documentation. Users must configure the environment to support AMP messaging protocols and maintain persistent markdown files for task tracking to leverage the full suite of memory and planning features.