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A Hermes "Digital Nervous System" — 28 Crons, 30+ Self-Built Skills

5 min read

Source: raw/reddit-1udesr1.md (r/hermesagent, u/HolmeBengt — “I’ve been asked many times what my Hermes actually does”, score 248)

A detailed, concrete account of one power user’s Hermes Agent deployment: 28 cron jobs and 30+ custom skills, every one built with Hermes rather than downloaded, forming what the author calls a “digital nervous system” for student life, business, health, and finances. It is one of the most specific real-world Hermes build logs the community has produced and a useful counterpoint to marketplace-skill workflows. Single-creator self-report (not independently verified), but the patterns are concrete and reusable.

The standout patterns

  • Dreaming (the memory hack). Every night at 3 AM, Hermes reads every conversation from the day, extracts decisions/projects/bugs/people/mistakes, and writes a structured summary to a file that auto-loads at the start of every session. The author’s key insight: the value isn’t the summarization, it’s where the output lands — a session-start context file. (Long-term recall is still called the biggest unsolved problem.)
  • Mail Gatekeeper (security model). Four inboxes filtered by a local AI judge running entirely on a Mac Mini via Ollama — no mail data touches an external API. 2FA codes, password resets, bank transactions, spam are quarantined; safe mail surfaces in a Telegram topic. There is no send endpoint anywhere in the system — Hermes can read and draft but nothing can physically leave the machine; a watchdog reviews blocked mail each evening for false positives. Runs across two separate Mac users for isolation.
  • Writing feedback loop (self-improving prompt). Every correction the author makes to Hermes’s writing is saved (before/after + why) to Notion; on Saturdays Hermes analyzes the collection for patterns and updates its own system prompt so the same feedback never has to be repeated.
  • Wisdom Vault → spaced repetition. Insightful links/voice notes/quotes are auto-extracted to Notion; on Sundays Hermes picks what’s worth memorizing and generates Anki cards (cloze / Q-A) that sync to the phone.

Other jobs in the system

  • Health Coach (noon): cross-references WHOOP recovery/strain/sleep/HRV + Apple Health + a self-built SQLite food tracker (logged via Telegram text/photo/barcode) against lean-bulk targets (2,300 cal / 150 g protein); iPhone lock-screen widget via Scriptable.
  • Study Audit (9 PM): Toggl Track time entries cross-referenced with a Notion chapter-checkbox DB → a daily learning audit (what studied, how long, which chapters done).
  • Finance Review: Sunday 6 PM + monthly on the 28th — pulls a self-hosted finance dashboard (MySalary) API for burn rate, P&L, net-worth trajectory, savings rate; delivered with voice.
  • Infrastructure monitoring (every 4h): site reachability, Coolify/VPS health, fail2ban flags, Mac Mini thermals (Ollama runs 24/7); full Hermes config backed up to iCloud each morning.
  • Daily status report (6:30 AM): calendar prep, open to-dos, system health, overnight anomalies — “the tactical dashboard, not the news.”

Build philosophy

  • Each skill is one file, one job, no dependencies. Outline goal + constraints → Hermes drafts approach + API choices → review/simplify → build v1 → test immediately (“it never works the first time”) → fix and simplify again.
  • Self-built beats downloaded. Marketplace/repo skills “never worked as well as what we built ourselves” — self-built tools fit the workflow organically and are debuggable because you shaped them.
  • Honest limitations: long-term session-to-session recall still inconsistent (Dreaming helps but isn’t enough); an Obsidian integration was built following the popular approach but “Hermes rarely reaches for it naturally”; 30+ skills = 30+ things that break on API/Hermes updates; mail polling adds ~2 min latency.

Key Takeaways

  • A concrete, end-to-end Hermes deployment: 28 crons + 30+ self-built single-file skills running a personal/business/health/finance “nervous system.”
  • Dreaming = nightly conversation→structured-summary written to an auto-loading session-start file; the lesson is where the summary lands, not the summarization.
  • Mail Gatekeeper is a strong local-first security pattern: Ollama judge on-device, no send endpoint exists, evening watchdog for false positives.
  • Self-improving writing loop: corrections → weekly pattern analysis → Hermes edits its own system prompt.
  • Build discipline: one file, one job, no dependencies; self-built skills beat downloaded ones for fit and debuggability.

Try It

  1. Steal Dreaming: add a nightly cron that summarizes the day’s sessions into a single context.md your agent loads at session start — the cheapest big win here.
  2. Local mail judge: run a small model in Ollama as a read-only inbox classifier with no send capability before letting any agent touch email.
  3. Close the writing loop: log every correction (before/after/why) and have the agent revise its own system prompt weekly.
  4. Keep skills single-file: one job, no dependencies — easier to debug when an upstream API or Hermes update breaks it.

Open Questions

  • How are the 28 crons scheduled/orchestrated to avoid contention (all on one Mac Mini + VPS)?
  • What model backs the Dreaming summarizer, and how large does the session-start context file grow before it strains the context window?
  • Exact false-positive rate of the Ollama mail judge (the watchdog implies it’s non-trivial).

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