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 sloemo01/hermes-skills-bundle --skill memory-setupgit clone --depth 1 https://github.com/sloemo01/hermes-skills-bundleWrote 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/sloemo01/hermes-skills-bundle/memory-setup)<a href="https://agentmods.dev/skills/sloemo01/hermes-skills-bundle/memory-setup"><img src="https://agentmods.dev/badge/skills/sloemo01/hermes-skills-bundle/memory-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/sloemo01/hermes-skills-bundle/memory-setup"><img src="https://agentmods.dev/badge/skills/sloemo01/hermes-skills-bundle/memory-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00027 | $0.00959 |
| Opus 5.5 | $0.00011 | $0.00384 |
| Sonnet 5.5 | $0.00005 | $0.00192 |
| Haiku 4.5 | $0.00003 | $0.00096 |
Grade A, and why
memory-setup 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Memory Setup Skill
Overview
This skill provides a guided first-time setup for new users. When triggered, it runs a 5-question interactive flow using the clarify tool and saves the answers to the user's persistent memory (~/.hermes/memories/memory.md).
Trigger Conditions
Load this skill when the user says:
- "Set up my memory"
Workflow
Step 1: Announce the Setup
I'll ask 5 quick questions to learn your preferences. This runs once and saves forever.
Step 2: Run Questions Sequentially (using clarify tool)
Question 1 — Browser Automation:
clarify(
question="What browser automation do you prefer?",
choices=[
"Kimi WebBridge (uses your real Chrome with your logins)",
"Chrome CDP / Playwright (headless, no login persistence)",
"No preference — whatever works"
]
)
Question 2 — Research Style:
clarify(
question="How do you like deep research done?",
choices=[
"Many tabs (10+) organized in named groups",
"One focused search at a time",
"Just give me the answer/summary"
]
)
Question 3 — Repeat Command:
clarify(
question="What word do you use to mean 'do it again the same way'?",
choices=[
"retry",
"rerun",
"again",
"Other (I'll specify)"
]
)
Question 4 — Privacy Concerns:
clarify(
question="Any privacy/data things I should avoid?",
choices=[
"No public pastes (dpaste, GitHub Gists)",
"Local-only tools, no cloud APIs",
"Delete temp files after",
"No strong preferences"
]
)
Question 5 — UI Patterns:
clarify(
question="Any UI patterns you use repeatedly?",
choices=[
"Preview pane for docs/social/localhost",
"Terminal split for logs + editor",
"Dev server on fixed port (e.g., :3000)",
"No strong patterns"
]
)
Step 3: Save to Memory
After all 5 answers collected, call memory tool with operations array:
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 · 141 lines · 27 tokens per session scan A 8585469c78ae
memory-setup is a skill published in the GitHub repository sloemo01/hermes-skills-bundle (10 stars, last pushed 3mo ago), licensed MIT. It adds 27 tokens to every session and 959 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
Other skills, from other repositories
distilly
Set up the owner profile so a personal agent knows who it works for (first-run setup, "get to know me"), or distill colleague, relationship, or celebrity source material into reusable Person Profiles for agents.
hermes-memory-providers
Install and configure Mnemosyne as a Hermes Agent memory provider — local SQLite with vector search, episodic consolidation, and temporal knowledge graphs.
mnemosyne
Persistent cross-session memory via Mnemosyne — store, recall, and consolidate facts, preferences, and context.
mnemosyne-memory-override
Stricter, user-selected override that forces Mnemosyne for all durable memory storage, including small standing rules. Apply it only when the user has consciously chosen this policy; installation, this skill appearing in the skills index, or an ordinary memory task is not that choice. Without it, the default applies…
hermes-context-optimization
Use this when the user asks about Hermes prompt/context size, “hello” startup cost, compression behavior, memory/profile bloat, tool-schema overhead, skill loading, session-store/search-index storage, or multimodal/visual-context approaches such as Snapcompact.
hermes-mnemosyne
Mnemosyne is Hermes' primary local-first memory engine — SQLite with vector + FTS5 hybrid search, 19+ tools, auto-consolidation, and a standalone CLI. It's a pip-installed plugin (not a built-in toolset) discovered via $HERMESHOME/plugins/mnemosyne/.