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 actual-setupgit 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/actual-setup)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/actual-setup"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/actual-setup/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/actual-setup"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/actual-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
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 →
- high Supply Chain · line 41 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium Data Exfiltration · line 55 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 94 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00016 | $0.01810 |
| Opus 5.5 | $0.00006 | $0.00724 |
| Sonnet 5.5 | $0.00003 | $0.00362 |
| Haiku 4.5 | $0.00002 | $0.00181 |
Grade C, and why
actual-setup scanned grade C with 2 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 1mo 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
(`curl -fsSL "https://actual.inc/install" | bash`) and completed device Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
(`curl -fsSL "https://actual.inc/install" | bash`) and completed device Copies of this mod
2 near-identical copies found in the catalogue:
- actual-setup — 100% identical, 0 lines differ
- actual-setup — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Actual Computer Setup Skill
Sets up actual.inc (Actual Computer) as a Hermes inference
provider. Actual turns the user's own hardware into a private inference cluster
and exposes an OpenAI-compatible API two ways: a hosted end-to-end-encrypted
relay at https://api.actual.inc (authenticated with an ac_ key), and a local
on-device daemon at http://127.0.0.1:8080 (no auth on loopback). This skill
does not install the Actual daemon for the user — device authorization requires
a human in a browser.
When to Use
- User wants to add actual.inc as an inference provider (cloud relay or local).
- User has an
ac_key and wants Hermes routed through their Actual cluster. - User wants fully-local, on-device inference via the Actual daemon.
- Troubleshooting: Actual requests failing with cryptic 400s or empty streams.
Prerequisites
- Hermes has first-class
actualprovider support (provider idactual, aliasesactual-computer,actualcomputer,aci). Do NOT configure Actual as acustom_providers/providers.actual.*entry on current Hermes — the built-in provider owns the name and handles base-url normalization, the Responses transport, and local no-auth automatically. - Relay mode: an Actual account and an
ac_inference key from https://actual.inc/user/keys. - Local mode: the user has installed the daemon
(
curl -fsSL "https://actual.inc/install" | bash) and completed device authorization by runningactualonce and opening the printedhttps://actual.inc/device?code=...URL in a browser. Relay that URL to the user and WAIT — never invent an email or authorize on their behalf. Codes expire in 5 minutes; re-runactualfor a fresh one.
How to Run
Relay / API mode
- Put the key in
.env(secrets only — never config.yaml): appendACTUAL_API_KEY=ac_...to~/.hermes/.env. - Verify the key and discover models with
terminal:curl -s https://api.actual.inc/v1/models -H "Authorization: Bearer $ACTUAL_API_KEY" - Select provider + model:
hermes config set model.provider actual hermes config set model.default "MODEL_ID_FROM_DISCOVERY" - Verify end-to-end:
hermes chat -Q -q "Reply with exactly: ACTUAL_OK" --provider actual -m MODEL_ID
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 148 lines · 16 tokens per session scan C 1b9e6bbfc5f4
actual-setup is a skill published in the GitHub repository NousResearch/hermes-agent (255,586 stars, last pushed today), licensed MIT. It adds 16 tokens to every session and 1,810 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
mle-workflow
Production machine-learning engineering workflow for data contracts, reproducible training, model evaluation, deployment, monitoring, and rollback. Use when building, reviewing, or hardening ML systems beyond one-off notebooks.
pytorch-patterns
PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.
claude-api
Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude…
caveman-discover
Find and label every LLM workflow in the repository so Caveman Cloud groups spend by workflow instead of one bucket. Use for "discover workflows" or breaking LLM spend down by workflow.
wearables_comms
Required for wearable-originated calls and text messages: resolve recipients for new calls and messages, and immediately answer, decline, or cancel calls on the originating wearable instead of silently switching to a paired phone.
withings
Use when linking Withings or reading Withings body measurements, activity, sleep, workout, heart, and intraday data.