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 searxng-searchgit 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/searxng-search)<a href="https://agentmods.dev/skills/nousresearch/hermes-agent/searxng-search"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/searxng-search/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/nousresearch/hermes-agent/searxng-search"><img src="https://agentmods.dev/badge/skills/nousresearch/hermes-agent/searxng-search.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Supply Chain · line 83 Remote code is downloaded and executed. This bypasses code review and could introduce malicious code.Fix: Avoid downloading and executing remote scripts. Use trusted packages from PyPI/npm. If remote fetch is required, verify checksums and use HTTPS.
- medium MCP Rug Pull · line 133 Docker image references without a specific tag (:latest is implicit) or digest (@sha256:...) can be silently replaced by a malicious image.Fix: Pin the image: image:tag or image@sha256:abc123
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 | $0.00018 | $0.01850 |
| Opus 5 | $0.00009 | $0.00925 |
| Sonnet 5 | $0.00004 | $0.00370 |
| Haiku 4.5 | $0.00002 | $0.00185 |
Grade A, and why
searxng-search scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s --max-time 5 "${SEARXNG_URL}/search?q=test&format=json" | head -c 200 Copies of this mod
6 near-identical copies found in the catalogue:
- searxng-search — 100% identical, 0 lines differ
- searxng-search — 100% identical, 0 lines differ
- searxng-search — 100% identical, 0 lines differ
- searxng-search — 92% identical, 21 lines differ
- searxng-search — 92% identical, 236 lines differ
- searxng-search — 92% identical, 21 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.
SearXNG Search
Free meta-search using SearXNG — a privacy-respecting, self-hosted search aggregator that queries 70+ search engines simultaneously.
No API key required when using a public instance. Can also be self-hosted for full control. Automatically appears as a fallback when the main web search toolset (FIRECRAWL_API_KEY) is not configured.
Configuration
SearXNG requires a SEARXNG_URL environment variable pointing to your SearXNG instance:
# Public instances (no setup required)
SEARXNG_URL=https://searxng.example.com
# Self-hosted SearXNG
SEARXNG_URL=http://localhost:8888
If no instance is configured, this skill is unavailable and the agent falls back to other search options.
Detection Flow
Check what is actually available before choosing an approach:
# Check if SEARXNG_URL is set and the instance is reachable
curl -s --max-time 5 "${SEARXNG_URL}/search?q=test&format=json" | head -c 200
Decision tree:
- If
SEARXNG_URLis set and the instance responds, use SearXNG - If
SEARXNG_URLis unset or unreachable, fall back to other available search tools - If the user wants SearXNG specifically, help them set up an instance or find a public one
Method 1: CLI via curl (Preferred)
Use curl via terminal to call the SearXNG JSON API. This avoids assuming any particular Python package is installed.
# Text search (JSON output)
curl -s --max-time 10 \
"${SEARXNG_URL}/search?q=python+async+programming&format=json&engines=google,bing&limit=10"
# With Safesearch off
curl -s --max-time 10 \
"${SEARXNG_URL}/search?q=example&format=json&safesearch=0"
# Specific categories (general, news, science, etc.)
curl -s --max-time 10 \
"${SEARXNG_URL}/search?q=AI+news&format=json&categories=news"
Common CLI Flags
| Flag | Description | Example |
|---|---|---|
q |
Query string (URL-encoded) | q=python+async |
format |
Output format: json, csv, rss |
format=json |
engines |
Comma-separated engine names | engines=google,bing,ddg |
limit |
Max results per engine (default 10) | limit=5 |
categories |
Filter by category | categories=news,science |
safesearch |
0=none, 1=moderate, 2=strict | safesearch=0 |
time_range |
Filter: day, week, month, year |
time_range=week |
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.
- 9d ago First seen · 196 lines · 18 tokens per session scan A 263b151f4277
searxng-search is a skill published in the GitHub repository NousResearch/hermes-agent (244,603 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 1,850 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
rubyllm
Build and maintain Ruby or Rails applications with the RubyLLM AI framework. Use for chats, agents, tools, structured output, media generation, transcription, OCR, moderation, embeddings, reranking, Rails integration, and RubyLLM upgrades; not for contributing to the framework itself.
rust-patterns
Idiomatic Rust patterns, ownership, error handling, traits, concurrency, and best practices for building safe, performant applications.
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…
deep-research
Multi-source deep research using firecrawl and exa MCPs. Searches the web, synthesizes findings, and delivers cited reports with source attribution. Use when the user wants thorough research on any topic with evidence and citations.
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.