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 grounded-citationsgit 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/grounded-citations)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/grounded-citations"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/grounded-citations.svg" alt="Measured on agentmods" height="20"></a>- Snyk warn
- 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 Rogue Agent · line 38 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
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 | $0.02987 |
| Opus 5 | $0.00008 | $0.01494 |
| Sonnet 5 | $0.00003 | $0.00597 |
| Haiku 4.5 | $0.00002 | $0.00299 |
Grade A, and why
grounded-citations scanned grade A with 1 finding 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 today.
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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
`browser_navigate`, or `terminal` (curl, CLIs). Copies of this mod
2 near-identical copies found in the catalogue:
- grounded-citations — 98% identical, 4 lines differ
- grounded-citations — 98% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grounded Citations
Every claim taken from an outside source gets an inline numbered citation and a
Sources: list, Perplexity-style. A ledger script owns the url → [n] mapping
so the numbers and URLs come from retrieval, never from memory — the model only
ever emits small integers it was handed.
For high-stakes work the same ledger doubles as a fact-checking chain: verbatim
quotes are attached to each source (rejected unless they literally appear in
the fetched page text), claims from model knowledge are flagged [unverified],
and verify --evidence fails any draft whose cited sources carry no evidence.
This skill covers answers in chat, written documents (markdown, PDF, docx,
slides), and research reports. It does not cover academic BibTeX pipelines —
for conference papers use the arxiv skill, which this skill
feeds (see references/citation-formats.md).
When to Use
Use whenever an answer or artifact rests on information you fetched rather than knew:
- Research, comparisons, news summaries, "what is the current state of X"
- Any deliverable you write to disk that quotes, paraphrases, or reports outside facts — reports, briefs, docs, decks, wiki pages
- Fact-finding where the user will want to check your work
- Multi-source synthesis where conflicting sources must be attributed
Skip inline citations when the retrieval is incidental to another task — a quick syntax/version lookup mid-coding, casual conversation, creative writing. Mention a URL only if the user would plausibly want the link.
Prerequisites
None beyond the standard toolset. scripts/sources.py is stdlib-only Python 3.
Retrieval comes from whatever is configured: web_search, web_extract,
browser_navigate, or terminal (curl, CLIs).
Ledger location: $HERMES_HOME/cache/citations/ledger.json (profile-aware).
Override per task with --ledger <path> or HERMES_CITATION_LEDGER.
How to Run
S=~/.hermes/skills/research/grounded-citations/scripts/sources.py
python "$S" reset # start a clean ledger
python "$S" add https://example.com/a --title "A" # prints: [1]
python "$S" add https://example.com/b --title "B" # prints: [2]
python "$S" list # ledger table
python "$S" render # Sources: block
python "$S" verify draft.md # catch bad citations
What ships with it
4 files 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.
- today Changed · +21 lines ef300e11c138
- 4d ago First seen · 233 lines · 16 tokens per session scan A 55083f47af62
grounded-citations is a skill published in the GitHub repository NousResearch/hermes-agent (242,680 stars, last pushed today), licensed MIT. It adds 16 tokens to every session and 2,987 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
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…
options
Present multiple design options as a vertical stack of anchored turns.
peek
Searches memories and displays compact one-liner results, or looks up a specific memory by ID. Use for quick memory lookups, checking if a decision was recorded, resolving [mem0:id] citations, or browsing memories without full category detail.
mem0-test-integration
Verify a Mem0 integration produced by /mem0-integrate. Runs in the same workspace on the same branch (loose coupling) — installs dependencies, runs the repo's native test suite, then exercises a real end-to-end smoke flow against the user's API key. Produces a scorecard. TRIGGER when: user has just run /mem0-integrate…
pptx
Create and validate Microsoft PowerPoint presentations (.pptx), including structured slide decks, tables, workflows, metadata, and reproducible generation scripts. Use for presentation, slides, PowerPoint, PPT, or PPTX creation and verification tasks.
safe-refactor
Restructure code while preserving behavior. Use for extraction, consolidation, ownership moves, or cleanup where verification must bracket structural edits.