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 agentmods add skills/nousresearch/hermes-agent/mapsnpx skills add NousResearch/hermes-agent --skill mapsgit 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/maps)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/maps"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/maps.svg" alt="Measured on agentmods" 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 | $0.00020 | $0.01740 |
| Opus 5 | $0.00010 | $0.00870 |
| Sonnet 5 | $0.00004 | $0.00348 |
| Haiku 4.5 | $0.00002 | $0.00174 |
Grade A, and why
maps 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 2d 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:
- maps — 100% identical, 0 lines differ
- maps — 100% identical, 42 lines differ
- maps — 100% identical, 42 lines differ
- maps — 100% identical, 42 lines differ
- maps — 100% identical, 0 lines differ
- maps — 100% identical, 42 lines differ
- maps — 100% identical, 42 lines differ
- maps — 100% identical, 42 lines differ
How it starts
The opening of the file, as written. The whole thing — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Maps Skill
Location intelligence using free, open data sources. 8 commands, 44 POI categories, zero dependencies (Python stdlib only), no API key required.
Data sources: OpenStreetMap/Nominatim, Overpass API, OSRM, TimeAPI.io.
This skill supersedes the old find-nearby skill — all of find-nearby's
functionality is covered by the nearby command below, with the same
--near "<place>" shortcut and multi-category support.
When to Use
- User sends a Telegram location pin (latitude/longitude in the message) →
nearby - User wants coordinates for a place name →
search - User has coordinates and wants the address →
reverse - User asks for nearby restaurants, hospitals, pharmacies, hotels, etc. →
nearby - User wants driving/walking/cycling distance or travel time →
distance - User wants turn-by-turn directions between two places →
directions - User wants timezone information for a location →
timezone - User wants to search for POIs within a geographic area →
area+bbox
Prerequisites
Python 3.8+ (stdlib only — no pip installs needed).
Script path: ~/.hermes/skills/maps/scripts/maps_client.py
Commands
MAPS=~/.hermes/skills/maps/scripts/maps_client.py
search — Geocode a place name
python $MAPS search "Eiffel Tower"
python $MAPS search "1600 Pennsylvania Ave, Washington DC"
Returns: lat, lon, display name, type, bounding box, importance score.
reverse — Coordinates to address
python $MAPS reverse 48.8584 2.2945
Returns: full address breakdown (street, city, state, country, postcode).
nearby — Find places by category
# By coordinates (from a Telegram location pin, for example)
python $MAPS nearby 48.8584 2.2945 restaurant --limit 10
python $MAPS nearby 40.7128 -74.0060 hospital --radius 2000
# By address / city / zip / landmark — --near auto-geocodes
python $MAPS nearby --near "Times Square, New York" --category cafe
python $MAPS nearby --near "90210" --category pharmacy
# Multiple categories merged into one query
python $MAPS nearby --near "downtown austin" --category restaurant --category bar --limit 10
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.
- 2d ago First seen · 196 lines · 20 tokens per session scan A 775ef9f79be9
maps is a skill published in the GitHub repository NousResearch/hermes-agent (241,505 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 1,740 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 2026-09-03.
Other skills, from other repositories
memory-triage
Persistent long-term memory protocol powered by mem0. Evaluate conversations for durable facts worth storing via memoryadd. Handles identity, preferences, decisions, configurations, rules, projects, and relationships. Loaded by the openclaw-mem0 plugin when skills mode is active.
mem0-dream
Consolidates stored memories by merging duplicates, resolving contradictions, and pruning stale entries. Use when memory count is high, search results feel noisy or repetitive, or periodic cleanup is needed to maintain memory quality.
mem0-vercel-ai-sdk
Mem0 provider for Vercel AI SDK (@mem0/vercel-ai-provider). TRIGGER when: user mentions "vercel ai sdk", "@mem0/vercel-ai-provider", "createMem0", "retrieveMemories", "addMemories", "getMemories", "searchMemories", "mem0 vercel", "AI SDK provider", "AI SDK memory", or is using generateText/streamText with mem0. Also…
mem0-tour
Browses all stored memories grouped by category with full content display. Use when reviewing all project memories, exploring stored knowledge, onboarding to a project, or getting an overview of captured decisions, conventions, and learnings.
onboard
Sets up mem0 for a new project including API key configuration, MCP authentication, project file import, and coding categories. Use on first run in a new project, when API key needs updating, or to re-run initial setup after configuration changes.
mem0-cli
Mem0 CLI -- the command-line interface for mem0 memory operations. TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli", "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get, mem0 init, mem0…