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/domain-intelnpx skills add NousResearch/hermes-agent --skill domain-intelgit 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/domain-intel)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/domain-intel"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/domain-intel.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 5.1 | $0.00020 | $0.01132 |
| Opus 5 | $0.00010 | $0.00566 |
| Sonnet 5 | $0.00004 | $0.00226 |
| Haiku 4.5 | $0.00002 | $0.00113 |
Grade A, and why
domain-intel 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 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- **Use `terminal` with `curl -I`** for a simple "is this URL reachable" check Copies of this mod
8 near-identical copies found in the catalogue:
- domain-intel — 100% identical, 0 lines differ
- domain-intel — 100% identical, 0 lines differ
- domain-intel — 92% identical, 21 lines differ
- domain-intel — 88% identical, 23 lines differ
- domain-intel — 88% identical, 24 lines differ
- domain-intel — 88% identical, 24 lines differ
- domain-intel — 88% identical, 24 lines differ
- domain-intel — 88% identical, 23 lines differ
How it starts
The opening of the file, as written. The whole thing — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain Intelligence — Passive OSINT
Passive domain reconnaissance using only Python stdlib. Zero dependencies. Zero API keys. Works on Linux, macOS, and Windows.
Helper script
This skill includes scripts/domain_intel.py — a complete CLI tool for all domain intelligence operations.
# Subdomain discovery via Certificate Transparency logs
python SKILL_DIR/scripts/domain_intel.py subdomains example.com
# SSL certificate inspection (expiry, cipher, SANs, issuer)
python SKILL_DIR/scripts/domain_intel.py ssl example.com
# WHOIS lookup (registrar, dates, name servers — 100+ TLDs)
python SKILL_DIR/scripts/domain_intel.py whois example.com
# DNS records (A, AAAA, MX, NS, TXT, CNAME)
python SKILL_DIR/scripts/domain_intel.py dns example.com
# Domain availability check (passive: DNS + WHOIS + SSL signals)
python SKILL_DIR/scripts/domain_intel.py available coolstartup.io
# Bulk analysis — multiple domains, multiple checks in parallel
python SKILL_DIR/scripts/domain_intel.py bulk example.com github.com google.com
python SKILL_DIR/scripts/domain_intel.py bulk example.com github.com --checks ssl,dns
SKILL_DIR is the directory containing this SKILL.md file. All output is structured JSON.
Available commands
| Command | What it does | Data source |
|---|---|---|
subdomains |
Find subdomains from certificate logs | crt.sh (HTTPS) |
ssl |
Inspect TLS certificate details | Direct TCP:443 to target |
whois |
Registration info, registrar, dates | WHOIS servers (TCP:43) |
dns |
A, AAAA, MX, NS, TXT, CNAME records | System DNS + Google DoH |
available |
Check if domain is registered | DNS + WHOIS + SSL signals |
bulk |
Run multiple checks on multiple domains | All of the above |
When to use this vs built-in tools
- Use this skill for infrastructure questions: subdomains, SSL certs, WHOIS, DNS records, availability
- Use
web_searchfor general research about what a domain/company does - Use
web_extractto get the actual content of a webpage - Use
terminalwithcurl -Ifor a simple "is this URL reachable" check
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 · 105 lines · 20 tokens per session scan A a212e30bced6
domain-intel is a skill published in the GitHub repository NousResearch/hermes-agent (242,093 stars, last pushed today), licensed MIT. It adds 20 tokens to every session and 1,132 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
rust-patterns
Idiomatic Rust patterns, ownership, error handling, traits, concurrency, and best practices for building safe, performant applications.
deployment-patterns
Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications. Use when setting up deployment infrastructure or planning releases.
golang-testing
Go testing best practices including table-driven tests, test helpers, benchmarking, race detection, coverage analysis, and integration testing patterns. Use when writing or improving Go tests.
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…
golang-patterns
Go-specific design patterns and best practices including functional options, small interfaces, dependency injection, concurrency patterns, error handling, and package organization. Use when working with Go code to apply idiomatic Go patterns.
verification-loop
A comprehensive verification system for Claude Code sessions. Use when verifying a Claude Code session's work before claiming it is complete.