Hermes Agent Curator: Automatic Agent Selection and Task Chaining

Key Takeaways

• Curator removes the need to manually select agents, tools, and models for each task — you describe what you want, and the system builds the team and runs the job.
• Three internal components: a task reader (understands the full intent, not just the surface ask), an agent picker (scores agents, tools, and models against each subtask), and a runner (chains outputs from one agent to the next).
• The agent picker learns from your acceptance and rejection patterns — the more you use Curator, the better its selections get for your specific workflow.
• Reported speed improvement: tasks that previously took 30 minutes now take around 5, primarily because the right agent is selected on the first try rather than after failed attempts.
• Works with any model Hermes supports: Claude, GPT, Gemini, and local models via Ollama.
• Hermes Agent is open-source and runs locally — Curator runs entirely on your own infrastructure.

How Curator Works: Three Components

The task reader parses your prompt to understand not just the words but the underlying goal. It distinguishes between a surface request ("write social posts") and the full job ("research what's trending in the space, draft posts for the next 30 days, schedule them across platforms"). The agent picker then looks at every agent you have configured, every tool available, and every model option, and scores them for each subtask. It picks the fastest and cheapest appropriate option, not just the most capable one. The runner executes the agents in order and passes each agent's output as input to the next — a research agent's findings go directly to a writer agent's context, which go directly to a reviewer agent, all without your involvement.

Practical Example: Monthly Content Plan

The demo use case: tell Curator to build a full content plan for next month. Curator deploys a research agent to find what's trending in your space, a writer agent to draft the posts, a planner agent to map publication dates, and a reviewer agent to check the work — all triggered by a single task prompt. This kind of multi-agent pipeline previously required manually configuring each agent, knowing which agent type handled which job, and sequencing the runs yourself. Curator collapses that setup into one step.

Related on OpenClawDatabase

• Hermes Agent Setup Guide — getting Hermes running on your VPS or Mac
• Hermes Tasks — scheduling and running automated tasks
• Hermes Memory — how Hermes stores and retrieves context
• Compare Agents — OpenClaw vs Hermes and other platforms