{"slug": "how-i-use-hermes-agent-to-run-an-agent-team", "title": "How I Use Hermes Agent to Run an Agent Team", "summary": "A developer runs more than ten Hermes agents across several servers for coding, project review, and decision-making, using Markdown \"anchor\" files as a control plane to manage the system and reduce cognitive load. The setup relies on Tailscale for private networking and Hermes cron jobs for silent security checks, with agents providing concise status reports that prioritize a \"best pick\" choice over raw data. A small ownership registry prevents conflicts when multiple agents work on the same projects.", "body_md": "I run more than ten Hermes agents across several servers.\n\nThat sounds powerful.\n\nI also got a real headache.\n\nSome agents write code. Some review project state. Some watch for problems. Some help me decide what to do next.\n\nThis is useful. It is also a lot to manage.\n\nThe hard part is not asking an agent to do work. The hard part is knowing:\n\nI have ADHD. Too many open loops can turn a good agent setup into stress.\n\nSo I use Hermes Agent as my control plane.\n\nBy \"control plane\", I mean the place where I check state, make a choice, and pick the next safe action.\n\nMy control plane is mostly Markdown files.\n\nI call them anchors.\n\nAn anchor is a small control sheet. It stores facts that should not live only in chat history.\n\nAn anchor can track:\n\nThis sounds boring. That is the point.\n\nBoring files are easy to read. They are easy to update. They are easy for Hermes to use in the next session.\n\nWithout anchors, each chat has to rebuild the world. With anchors, Hermes can check the files, update them, and give me a short answer.\n\nThe goal is not more notes. The goal is less load on my brain.\n\nThe loop looks like this:\n\n```\nme on Telegram\n  ↓\nHermes Gateway\n  ↓\nClaw, one of my Hermes agents\n  ↓\nSSH checks over Tailscale + files + cron + memory + skills + session search\n  ↓\nMarkdown anchors\n  ↓\nshort report: best pick, blocker, next action\n```\n\nHermes Agent works well here because it is not just chat.\n\nIt can use tools. It can read and write files. It can run shell commands. It can run cron jobs. It has memory. It can search old sessions. It can use skills.\n\nThat mix makes it useful for daily ops.\n\nOne boring but important piece is Tailscale.\n\nMy agents and servers are not all on one public machine. Tailscale gives them a private network with stable names and safe access paths. That makes managing many agents much easier:\n\nFor me, Hermes is the control plane and Tailscale is the private road between the machines.\n\nI often ask:\n\n```\ncodex status?\n```\n\nHermes checks several worker nodes. It reads the live model limits. It updates the capacity anchor. Then it gives me a short routing answer.\n\nHere is a redacted example:\n\n```\nBest pick: node-c\nFallback: node-d\n\n- node-a / control-node / account-a\n  GPT-5.5: 33%, reset 20:14\n  Spark: 91%, reset 6/3 14:57\n\n- node-b / worker-node / account-b\n  GPT-5.5: 12%, reset 20:13\n  Spark: 100%, reset 6/6 02:11\n\n- node-c / worker-node / account-c\n  GPT-5.5: 75%, reset 5/31 10:52\n  Spark: 100%, reset 6/6 02:11\n\n- node-d / worker-node / account-d\n  GPT-5.5: 66%, reset 23:30\n  Spark: 100%, reset 6/6 02:11\n```\n\nThe key part is \"Best pick\" at the top.\n\nI do not want a wall of data. I want the choice first, then enough proof to trust it.\n\nI also use Hermes cron jobs for checks that should stay quiet when all is well.\n\nA security check might look at:\n\nIf all checks pass, it sends nothing.\n\nIf something is wrong, it sends a short alert:\n\n```\nauditd watchdog\n\nnode-c:\n- audit log is too large\n- next: rotate the log and check auditd again\n```\n\nThis matters.\n\nIf a reminder says \"all good\" every day, I learn to ignore it. Quiet success saves attention for real problems.\n\nWhen many agents work at once, ownership can get messy.\n\nSo I keep a small registry:\n\n```\nClaw\n- Role: control plane, QA, memory keeper, ops helper.\n- Work: maintain anchors, route model work, read monitoring reports.\n\nBuilder Agent\n- Role: main builder for project-alpha.\n- Rule: Claw can inspect and report, but should not take over unless asked.\n\nnode-c / worker-node\n- Role: best node for long work right now.\n- Note: check ownership before touching active project folders.\n```\n\nThis stops a common problem: two helpful agents changing the same repo because nobody wrote down who owns it.\n\nA good Claw report is small:\n\n```\nAnswer first.\nEvidence second.\nBlocker only if real.\nOne next action.\n```\n\nThis is not just style. It is part of the system.\n\nFor me, support means:\n\nHermes can take on a lot of that load.\n\nYou do not need ten agents to use this idea.\n\nStart with one file:\n\n```\n# agent-team-anchor.md\n\n## Current owner\nClaw\n\n## Active agents\n- Builder: owns project-alpha\n- Reviewer: reviews pull requests only\n- Ops: checks servers and cron\n\n## Safe next action\nAsk Claw to summarize blockers and pick one next step.\n\n## Do not touch\n- active production deploys\n- repos owned by another agent\n```\n\nThen ask Hermes:\n\n```\nRead agent-team-anchor.md.\n\nUpdate stale facts if needed.\n\nTell me:\n1. best next action\n2. real blocker, if any\n3. which agent owns the work\n\nKeep it under 8 lines.\n```\n\nThat is the smallest version of my control plane.\n\nIf an agent only uses chat history, it will miss things. Put the current state in a file.\n\nNot every fact belongs in long term memory.\n\nI split it like this:\n\nThat keeps memory clean.\n\nA cron job should help me act. If it has nothing useful to say, it should stay silent.\n\nI do not publish real host names, account names, IPs, tokens, or private project names.\n\nThe public examples keep the shape of the work, not the private details.\n\nDashboards are good when I need to dig.\n\nFor daily work, a short message is often better:\n\n```\nBest pick: node-c.\nBlocker: node-b is low on capacity.\nNext: send long work to node-c.\n```\n\nI want to make the anchor files easier to check.\n\nNext steps:\n\nI would still keep Markdown as the base.\n\nA human should be able to open the file and understand what is going on.\n\nI wrote this article with help from Hermes Agent itself.\n\nThe examples are redacted from a real workflow. I changed host names, account names, IPs, session IDs, and project names.\n\nHermes Agent is an open source project by Nous Research. Claw is my own way of using Hermes Agent as a daily control plane.\n\nHermes did not give me more agents.\n\nIt gave me a way to see what my agents are doing.\n\nThe agents check, write, route, remember, and report. I still choose what matters, what is safe, and what should happen next.\n\nMy headache is getting better.\n\nThat is the difference between having many agents and having a working agent team.", "url": "https://wpnews.pro/news/how-i-use-hermes-agent-to-run-an-agent-team", "canonical_source": "https://dev.to/askclaw/how-i-use-hermes-agent-to-run-an-agent-team-503g", "published_at": "2026-05-30 11:36:31+00:00", "updated_at": "2026-05-30 12:12:50.721349+00:00", "lang": "en", "topics": ["ai-agents", "ai-tools", "ai-infrastructure", "artificial-intelligence"], "entities": ["Hermes Agent", "Hermes Gateway", "Claw", "Telegram", "Tailscale", "SSH", "Markdown"], "alternates": {"html": "https://wpnews.pro/news/how-i-use-hermes-agent-to-run-an-agent-team", "markdown": "https://wpnews.pro/news/how-i-use-hermes-agent-to-run-an-agent-team.md", "text": "https://wpnews.pro/news/how-i-use-hermes-agent-to-run-an-agent-team.txt", "jsonld": "https://wpnews.pro/news/how-i-use-hermes-agent-to-run-an-agent-team.jsonld"}}