Hermes One is a desktop application for installing, configuring, and chatting with Hermes Agent, an AI assistant that uses tools, memory, skills, scheduling, and messaging integrations. It is for people who want to manage Hermes Agent through a graphical interface, and the catalogue entries support its workflows with skills, hooks, instructions, and settings.
Borrowing it
Nothing to install: this file belongs to fathah/hermes-desktop. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/fathah/hermes-desktop/main/AGENTS.mdgit clone --depth 1 https://github.com/fathah/hermes-desktopWrote 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/instructions/fathah/hermes-desktop/agents-md)<a href="https://agentmods.dev/instructions/fathah/hermes-desktop/agents-md"><img src="https://agentmods.dev/badge/instructions/fathah/hermes-desktop/agents-md/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/instructions/fathah/hermes-desktop/agents-md"><img src="https://agentmods.dev/badge/instructions/fathah/hermes-desktop/agents-md.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 | $0.01250 | $0.01250 |
| Opus 5.5 | $0.00500 | $0.00500 |
| Sonnet 5.5 | $0.00250 | $0.00250 |
| Haiku 4.5 | $0.00125 | $0.00125 |
Grade A, and why
hermes-desktop AGENTS.md 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- hermes-desktop CLAUDE.md — 100% identical, 0 lines differ
- lat.md AGENTS.md — 86% identical, 41 lines differ
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Before starting work
- Run
lat searchto find sections relevant to your task. Read them to understand the design intent before writing code. - Run
lat expandon user prompts to expand any[[refs]]— this resolves section names to file locations and provides context.
Post-task checklist (REQUIRED — do not skip)
After EVERY task, before responding to the user:
- Update
lat.md/if you added or changed any functionality, architecture, tests, or behavior - Run
lat check— all wiki links and code refs must pass - Do not skip these steps. Do not consider your task done until both are complete.
What is lat.md?
This project uses lat.md to maintain a structured knowledge graph of its architecture, design decisions, and test specs in the lat.md/ directory. It is a set of cross-linked markdown files that describe what this project does and why — the domain concepts, key design decisions, business logic, and test specifications. Use it to ground your work in the actual architecture rather than guessing.
Commands
lat locate "Section Name" # find a section by name (exact, fuzzy)
lat refs "file#Section" # find what references a section
lat search "natural language" # semantic search across all sections
lat expand "user prompt text" # expand [[refs]] to resolved locations
lat check # validate all links and code refs
Run lat --help when in doubt about available commands or options.
If lat search fails because no API key is configured, explain to the user that semantic search requires a key provided via LAT_LLM_KEY (direct value), LAT_LLM_KEY_FILE (path to key file), or LAT_LLM_KEY_HELPER (command that prints the key). Supported key prefixes: sk-... (OpenAI) or vck_... (Vercel). If the user doesn't want to set it up, use lat locate for direct lookups instead.
Syntax primer
- Section ids:
lat.md/path/to/file#Heading#SubHeading— full form uses project-root-relative path (e.g.lat.md/tests/search#RAG Replay Tests). Short form uses bare file name when unique (e.g.search#RAG Replay Tests,cli#search#Indexing). - Wiki links:
[[target]]or[[target|alias]]— cross-references between sections. Can also reference source code:[[src/foo.ts#myFunction]]. - Source code links: Wiki links in
lat.md/files can reference functions, classes, constants, and methods in TypeScript/JavaScript/Python/Rust/Go/C files. Use the full path:[[src/config.ts#getConfigDir]],[[src/server.ts#App#listen]](class method),[[lib/utils.py#parse_args]],[[src/lib.rs#Greeter#greet]](Rust impl method),[[src/app.go#Greeter#Greet]](Go method),[[src/app.h#Greeter]](C struct).lat checkvalidates these exist. - Code refs:
// @lat: [[section-id]](JS/TS/Rust/Go/C) or# @lat: [[section-id]](Python) — ties source code to concepts
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 · 106 lines · 1,250 tokens per session scan A 5fd49383be7f
hermes-desktop AGENTS.md is an instructions file published in the GitHub repository fathah/hermes-desktop (14,431 stars, last pushed 7d ago), licensed MIT. It adds 1,250 tokens to every session, about $0.0050 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 2026-08-30.
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