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A community collection of real-world Hermes Agent use cases — each one backed by public evidence.
This Catalog
Official Docs
X Threads
Reddit
Organized by category
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Partial
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Runnable demos included
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Primary source required
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Community-maintained
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Note
Evidence rule. Every use case here links to a primary source: an official Hermes doc, a Nous Research companion repo, a GitHub issue with deployment details, or a first-person blog post. If the only evidence is a tweet or "community build" marketing page, it lives in research/unverified.md instead — not in the catalog below.
A scheduled agent that researches topics every morning and delivers a summary to Telegram or Discord. The canonical "hello world" of Hermes automation.
Always-on shared bot for a small team — coding, research, ops — with per-user sessions, Docker-isolated terminal, and an allowlist. The gateway also supports Discord, Slack, WhatsApp, Signal, Matrix, Email, SMS, and more; the Telegram flow is the cleanest starting point for any of them.
End-to-end autonomous novel, art, and audiobook production. Nous Research's own pipeline shipped a 19-chapter, 79,456-word book with an audiobook and a website.
Feed Hermes a raw screen recording and get a finished tutorial video on HeyGen with your AI avatar — script generation, video production, and memory of preferences for repeat work.
Install, launch, and run ComfyUI node-based media generation workflows on demand — from Stable Diffusion to video pipelines, with automatic custom-node installation and deterministic output management.
Hermes writes designed HTML compositions (via Open Design), then renders to MP4 via HyperFrames — GSAP animations, shader transitions, TTS narration, all code-driven with no timeline editor.
Hermes as one of four interchangeable executors (Claude Code, Codex, Gemini, Hermes) inside a third-party multi-agent orchestrator. Bash-bridge adapter pattern with shared identity.
Use Matt Pocock's open-source skills (/grill-me, /to-prd, /to-issues) for planning and scoping, then Hermes sub-agents for parallel implementation of vertical-sliced issues — with HITL gates to stop AI slop before it ships.
A monitoring and improvement loop that reads session history, ranks weak skills, proposes patches or new skills, invokes self-evolution, and reports learning progress.
Replace or augment native memory with a dedicated cognitive DB — vector + knowledge graph + temporal decay + contradiction detection. Integrates over MCP, so no Hermes plugin needed.
Wire Hermes into an Obsidian vault for persistent knowledge — read notes, create daily dashboards, cross-reference tags, maintain a self-improving personal knowledge base.
A read-only dashboard plugin that turns prompts, tool calls, failures, approvals, model switches, cron runs, and memory hits into auditable agent journeys.
A Kali-backed Hermes skill for authorized security assessments with scope confirmation, playbooks, zero-findings fallback, approval gates, and structured reports.
Autonomous weather prediction-market trading — Kelly Criterion position sizing, EV scoring against market odds, self-calibrating with real traders reporting $300→$123K in 3 months on a $5 VPS.
Hermes probes your local inference server, identifies the running model, detects context window, and auto-configures — eliminates first-setup friction for Ollama, llama.cpp, MLX, and vLLM.
Run a single query across Reddit, X/Twitter, YouTube, Hacker News, and Polymarket via a single Python engine. Firefox-cookie auth for X, no API key needed on WSL. Delivered as a unified markdown brief to Telegram or local storage.
See CONTRIBUTING.md. The short version: one primary source minimum — official docs, a Nous companion repo, a GitHub issue with real deployment detail, or a first-person blog post. X posts and "community build" marketing pages don't count as primary evidence.
For Contributors
Every PR that touches usecases/*.md triggers automated verification. Learn how it works and how to pass it:
docs/verification-criteria.md — how scoring works, what's green vs yellow vs red, and how to run the script locally before submitting
python scripts/verify-usecase.py --usecase usecases/my-topic.md --check all — generate your own verification report
Please only submit use cases you have personally run (at least once) or that you can trace to a primary public source. No crypto use cases.
License
MIT for code and configs. Docs and diagrams under CC BY 4.0.
