Agent37 is Nous's hosted Hermes from $3.99/mo. Self-host runs $4-8/mo on a VPS plus ops. Decide with cost, compliance, data locality, and ops capacity in mind.
Your Claude Code CLAUDE.md is static project context. Hermes memory is dynamic and agent-curated. Here is how to move between them without losing signal.
Hermes ships devops and mlops skill categories. Tour representative skills and watch them chain through a typical incident — alert to rollback — with Claude in the loop.
Step-by-step port of a write-changelog skill from Claude Code to Hermes. Original file, target file, line-by-line what changes and why.
Tour the red-teaming skill category that ships with Hermes Agent. What each category of skill does, responsible-use norms, and how skills chain in an engagement.
Step-by-step setup for the hermes-acp entry point in VS Code, Zed, and JetBrains. Get a persistent Hermes agent panel inside your editor.
Two ways Hermes talks to Claude Code: claude -p print mode and tmux-backed PTY sessions. When to use each, what they cost, where they break.
Hermes ships with a bundled skill that teaches it to delegate heavy coding work to Claude Code. Here is how the delegate_task() pattern works in practice.
Claude Code is your IDE agent. Hermes is your server-side agent. Here is how to decide which tool fits which job, and why most teams end up using both.
OpenClaw extends Claude Code inside its runtime. Hermes runs a second, Python-based runtime that calls Claude. Compare philosophies, layers, and where each fits.
Short answer: yes, format-compatible. Long answer: there are a few differences in frontmatter, triggers, and related-skills resolution. Here is what to change.
Model Context Protocol is identical in both runtimes. What differs is the host lifecycle. Compare filesystem, GitHub, and Postgres MCP servers side by side.
Learn how to design skills that guide Claude's tool usage. Master when to invoke tools, how to interpret results, and tool-aware skill patterns.
Build Level 3 AI skills that leverage tools for file access, API integration, and system interaction. The gateway to powerful, practical automation.
Build AI agents that select and invoke external tools. Learn tool definition, parameter extraction, result handling, and error recovery patterns.
Master the router pattern for AI agents. Learn how LLMs decide execution paths, implement conditional logic, and build intelligent routing systems.
Learn to build Level 2 AI skills that use templates and placeholders for structured, consistent output generation across documents, code, and content.
Design AI skill outputs that are consistent, parseable, and useful. Master output format specification for reliable, actionable results.
Design and implement multi-agent systems. Learn orchestration patterns, agent communication, task delegation, and building collaborative AI teams.
Master the multi-agent design pattern. Learn how to build systems where specialized agents collaborate to solve complex problems together.
Learn how to implement effective guardrails and constraints in AI skills to ensure reliable, safe, and predictable behavior in production environments.
Master the art of composable AI skills. Learn patterns for building modular, reusable skill components that combine into powerful workflows.
Learn how to build systems where multiple AI agents collaborate. Patterns for coordination, delegation, and collective intelligence.
Learn to design AI skills with focused, clear purposes. Master the art of scoping skills for maximum effectiveness and minimum overlap.
Understand Level 1 agents - the foundation of agentic systems. Learn when simple responders are enough and how to build them effectively.
Explore fully autonomous AI agents that generate and execute code independently. Learn safety patterns, supervision strategies, and responsible autonomy design.
Master Level 1 AI skills that enhance prompts through tone, style, and vocabulary adjustments. The simplest skills with the fastest path to value.
Master the art of integrating tools into AI agents. Learn tool design, MCP servers, custom tools, and best practices for connecting agents to the real world.
Build Level 4 AI skills that coordinate multiple specialized agents for complex tasks. Master delegation, communication, and result synthesis.
Understand how memory transforms AI agents from stateless responders to intelligent systems that learn and remember. Implement all three memory types.
Learn how to implement guardrails that keep AI agents on track. Prevent harmful outputs, maintain boundaries, and ensure reliable agent behavior.
Master context injection techniques to teach Claude domain-specific knowledge. Learn to inject conventions, rules, and expertise effectively.
Learn how role-playing techniques dramatically improve AI agent performance. Specific roles, personas, and contexts lead to better results.
Build Level 5 AI skills that operate autonomously with self-directed execution, adaptive decision-making, and minimal human intervention.
Why specialized agents outperform general-purpose ones. Learn how to design focused agents that excel at specific tasks.