Hermes Agent is an AI assistant that learns from its use by creating and improving skills, retaining knowledge, searching past conversations, and adapting to its users. It is for people who want to run an agent through a terminal or messaging platforms while connecting it to different AI models and scheduled tasks.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add NousResearch/hermes-agent --skill pokemon-playergit clone --depth 1 https://github.com/NousResearch/hermes-agentWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nousresearch/hermes-agent/pokemon-player)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/pokemon-player"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/pokemon-player/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/pokemon-player"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/pokemon-player.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 215 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00013 | $0.02194 |
| Opus 5 | $0.00006 | $0.01097 |
| Sonnet 5 | $0.00003 | $0.00439 |
| Haiku 4.5 | $0.00001 | $0.00219 |
Grade A, and why
pokemon-player scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
8 near-identical copies found in the catalogue:
- pokemon-player — 100% identical, 0 lines differ
- pokemon-player — 100% identical, 0 lines differ
- pokemon-player — 94% identical, 19 lines differ
- pokemon-player — 94% identical, 16 lines differ
- pokemon-player — 94% identical, 16 lines differ
- pokemon-player — 94% identical, 16 lines differ
- pokemon-player — 94% identical, 16 lines differ
- pokemon-player — 94% identical, 19 lines differ
How it starts
The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pokemon Player
Play Pokemon games via headless emulation using the pokemon-agent package.
When to Use
- User says "play pokemon", "start pokemon", "pokemon game"
- User asks about Pokemon Red, Blue, Yellow, FireRed, etc.
- User wants to watch an AI play Pokemon
- User references a ROM file (.gb, .gbc, .gba)
Startup Procedure
1. First-time setup (clone, venv, install)
The repo is NousResearch/pokemon-agent on GitHub. Clone it, then set up a Python 3.10+ virtual environment. Use uv (preferred for speed) to create the venv and install the package in editable mode with the pyboy extra. If uv is not available, fall back to python -m venv + pip.
If a checkout already exists (e.g. ~/pokemon-agent with a venv ready), just cd there and source .venv/bin/activate instead of recloning.
You also need a ROM file. Ask the user for theirs (a previous setup may already have one at roms/pokemon_red.gb inside the checkout). NEVER download or provide ROM files — always ask the user.
2. Start the game server
From inside the pokemon-agent directory with the venv activated, run pokemon-agent serve with --rom pointing to the ROM and --port 9876. Run it in the background with &. To resume from a saved game, add --load-state with the save name. Wait 4 seconds for startup, then verify with GET /health.
3. Set up live dashboard for user to watch
Use an SSH reverse tunnel via localhost.run so the user can view the dashboard in their browser. Connect with ssh, forwarding local port 9876 to remote port 80 on the keyless localhost.run endpoint (ssh -R 80:localhost:9876 ssh://[email protected]). Redirect output to a log file, wait 10 seconds, then grep the log for the .lhr.life URL. Give the user the URL with /dashboard/ appended. The tunnel URL changes each time — give the user the new one if restarted.
Save and Load
When to save
- Every 15-20 turns of gameplay
- ALWAYS before gym battles, rival encounters, or risky fights
- Before entering a new town or dungeon
- Before any action you are unsure about
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 221 lines · 13 tokens per session scan A 510a053f2ca5
pokemon-player is a skill published in the GitHub repository NousResearch/hermes-agent (243,598 stars, last pushed today), licensed MIT. It adds 13 tokens to every session and 2,194 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
pokemon-player
Play Pokemon games autonomously via headless emulation. Starts a game server, reads structured game state from RAM, makes strategic decisions, and sends button inputs — all from the terminal.
pokemon-player
Play Pokemon via headless emulator + RAM reads.
pokemon-player
Play Pokemon via headless emulator + RAM reads.
pokemon-player
Play Pokemon games autonomously via headless emulation. Starts a game server, reads structured game state from RAM, makes strategic decisions, and sends button inputs — all from the terminal.
pokemon-player
Play Pokemon games autonomously via headless emulation. Starts a game server, reads structured game state from RAM, makes strategic decisions, and sends button inputs — all from the terminal.
pokemon-player
Play Pokemon games autonomously via headless emulation. Starts a game server, reads structured game state from RAM, makes strategic decisions, and sends button inputs — all from the terminal.