Trending-skills awesome-hermes-agent

```markdown

install
source · Clone the upstream repo
git clone https://github.com/Aradotso/trending-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/Aradotso/trending-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/awesome-hermes-agent" ~/.claude/skills/aradotso-trending-skills-awesome-hermes-agent && rm -rf "$T"
manifest: skills/awesome-hermes-agent/SKILL.md
source content
---
name: awesome-hermes-agent
description: Curated ecosystem guide for Hermes Agent by Nous Research — a self-improving AI agent with skills, memory, multi-platform messaging, and MCP integration
triggers:
  - "help me set up Hermes Agent"
  - "how do I install skills for Hermes"
  - "configure Hermes Agent for my project"
  - "add a skill to Hermes"
  - "Hermes Agent deployment and integrations"
  - "use Hermes with Telegram or Discord"
  - "what skills are available for Hermes Agent"
  - "Nous Research Hermes Agent workflow"
---

# Awesome Hermes Agent

> Skill by [ara.so](https://ara.so) — Daily 2026 Skills collection.

A curated ecosystem of skills, tools, integrations, and resources for [Hermes Agent](https://github.com/NousResearch/hermes-agent) by Nous Research — the self-improving AI agent with a closed learning loop, multi-platform gateway support, and a growing skills ecosystem.

---

## What Is Hermes Agent?

Hermes Agent is a self-improving AI agent that:

- **Creates skills from experience** — learns and stores reusable capabilities as procedural memory
- **Improves skills during use** — refines skills automatically through feedback loops
- **Searches past conversations** — episodic memory across sessions
- **Builds a model of you** — deepening user context over time
- **Runs anywhere** — $5 VPS, GPU cluster, or serverless; talk to it via Telegram while it works on a cloud VM
- **Supports MCP** — integrates with Model Context Protocol tool servers
- **Schedules tasks** — built-in cron scheduling
- **Multi-platform messaging** — Telegram, Discord, Slack, WhatsApp, Signal

---

## Installation

### Quick Start (Official)

Follow the [Official Docs quickstart](https://hermes-agent.nousresearch.com/docs/) for the authoritative installation guide.

```bash
# Clone the core project
git clone https://github.com/NousResearch/hermes-agent
cd hermes-agent

# Install dependencies (Python-based)
pip install -e .

# Or with uv (faster)
uv pip install -e .

Environment Configuration

# Copy example config
cp .env.example .env

# Required: Set your model provider API key
export OPENAI_API_KEY=your_key_here        # or
export ANTHROPIC_API_KEY=your_key_here    # or
export OPENROUTER_API_KEY=your_key_here

# Optional: Telegram gateway
export TELEGRAM_BOT_TOKEN=your_token_here

# Optional: Discord gateway
export DISCORD_BOT_TOKEN=your_token_here

Minimal
.env
Example

# Model backend
OPENROUTER_API_KEY=sk-or-...
DEFAULT_MODEL=openai/gpt-4o

# Memory / skills storage
HERMES_DATA_DIR=~/.hermes

# Messaging gateway (pick one or more)
TELEGRAM_BOT_TOKEN=...
DISCORD_BOT_TOKEN=...

Key CLI Commands

# Start an interactive session
hermes chat

# Run in daemon mode (background, messaging gateway active)
hermes serve

# List installed skills
hermes skills list

# Install a skill from a path or URL
hermes skills install ./my-skill
hermes skills install https://github.com/user/repo

# Run a single task non-interactively
hermes run "summarize the last 10 git commits"

# Search conversation memory
hermes memory search "database migration"

# Show agent status
hermes status

# Cron: list scheduled tasks
hermes cron list

# Cron: add a task
hermes cron add "0 9 * * *" "send me a daily briefing"

Skills Architecture

Skills are the core of the Hermes learning loop. A skill is a reusable capability stored as structured memory.

Skill File Format (
SKILL.md
)

---
name: my-skill
description: Does X given Y
triggers:
  - "do X"
  - "help me with Y"
---

# My Skill

## Instructions
...step-by-step instructions the agent follows...

## Examples
...worked examples...

Installing Community Skills

# Install wondelai/skills (cross-platform, 250+ skills)
git clone https://github.com/wondelai/skills ~/.hermes/skills/wondelai
hermes skills reload

# Install cybersecurity skills (MITRE ATT&CK mapped)
git clone https://github.com/mukul975/Anthropic-Cybersecurity-Skills ~/.hermes/skills/cybersec
hermes skills reload

Creating a Skill Programmatically

from hermes_agent import HermesAgent, Skill

agent = HermesAgent()

# Define a new skill
skill = Skill(
    name="git-summarize",
    description="Summarizes recent git activity",
    triggers=["summarize git", "what changed recently", "git digest"],
    instructions="""
    1. Run `git log --oneline -20`
    2. Group commits by type (feat, fix, chore, etc.)
    3. Return a concise bullet-point summary
    """,
)

agent.skills.register(skill)
agent.skills.save()  # persists to HERMES_DATA_DIR

Core Python API

from hermes_agent import HermesAgent

# Initialize agent (picks up .env automatically)
agent = HermesAgent()

# Single-turn query
response = await agent.chat("What files did I work on yesterday?")
print(response.text)

# Multi-turn conversation
session = agent.new_session()
r1 = await session.send("I'm building a FastAPI app")
r2 = await session.send("Add authentication to it")  # has context from r1

# Access memory
memories = agent.memory.search("FastAPI authentication")
for m in memories:
    print(m.summary, m.created_at)

# Trigger a skill explicitly
result = await agent.skills.run("git-summarize", context={"repo": "/path/to/repo"})

# Schedule a cron task
agent.cron.add(
    schedule="0 8 * * 1-5",  # weekdays at 8am
    task="send me a standup prompt with yesterday's git activity",
)

MCP Integration

Hermes supports Model Context Protocol servers as tool backends.

from hermes_agent import HermesAgent
from hermes_agent.mcp import MCPServer

agent = HermesAgent()

# Register an MCP server
agent.mcp.register(
    MCPServer(
        name="filesystem",
        command="npx",
        args=["-y", "@modelcontextprotocol/server-filesystem", "/home/user/projects"],
    )
)

# The agent can now use filesystem MCP tools in any conversation
response = await agent.chat("List all Python files in my projects folder")
# Or configure in hermes.yaml
mcp:
  servers:
    - name: filesystem
      command: npx
      args: ["-y", "@modelcontextprotocol/server-filesystem", "/home/user/projects"]
    - name: github
      command: npx
      args: ["-y", "@modelcontextprotocol/server-github"]
      env:
        GITHUB_PERSONAL_ACCESS_TOKEN: "${GITHUB_TOKEN}"

Configuration Reference (
hermes.yaml
)

# hermes.yaml — place in project root or ~/.hermes/

model:
  default: openai/gpt-4o
  fallback: openai/gpt-4o-mini
  temperature: 0.7

memory:
  backend: sqlite          # sqlite | postgres | chroma
  data_dir: ~/.hermes
  max_context_turns: 50

skills:
  directories:
    - ~/.hermes/skills
    - ./skills
  auto_improve: true       # refine skills after use

gateway:
  telegram:
    enabled: true
    token: "${TELEGRAM_BOT_TOKEN}"
    allowed_users: ["your_telegram_id"]
  discord:
    enabled: false
    token: "${DISCORD_BOT_TOKEN}"

cron:
  enabled: true
  timezone: America/New_York

terminal:
  backend: local           # local | docker | e2b | modal | ssh | k8s

Deployment Patterns

Local Development

# Simple local run
hermes chat

# With a specific model
HERMES_MODEL=anthropic/claude-3-5-sonnet hermes chat

Docker

FROM python:3.12-slim
WORKDIR /app
COPY . .
RUN pip install hermes-agent

ENV HERMES_DATA_DIR=/data
VOLUME ["/data"]

CMD ["hermes", "serve"]
docker run -d \
  -e OPENROUTER_API_KEY=$OPENROUTER_API_KEY \
  -e TELEGRAM_BOT_TOKEN=$TELEGRAM_BOT_TOKEN \
  -v hermes-data:/data \
  my-hermes-agent

Serverless (Modal)

import modal
from hermes_agent import HermesAgent

app = modal.App("hermes-agent")

@app.function(
    secrets=[modal.Secret.from_name("hermes-secrets")],
    timeout=300,
)
async def run_task(prompt: str) -> str:
    agent = HermesAgent()
    response = await agent.chat(prompt)
    return response.text

Remote Terminal Backend (SSH to cloud VM)

# hermes.yaml
terminal:
  backend: ssh
  ssh:
    host: your-vm.example.com
    user: ubuntu
    key_path: ~/.ssh/id_ed25519

Multi-Agent Patterns

Using mission-control for Fleet Management

# Install mission-control (3k+ stars, broad agent orchestration)
git clone https://github.com/builderz-labs/mission-control
cd mission-control && npm install && npm run dev
# Then register your Hermes instance in the dashboard

Inter-Agent Bridge (hermes-plugins)

# Install hermes-plugins for inter-agent communication
git clone https://github.com/42-evey/hermes-plugins ~/.hermes/plugins/42-evey
hermes plugins reload
# Send a task from one Hermes instance to another
from hermes_agent.plugins import InterAgentBridge

bridge = InterAgentBridge(target_agent_url="http://agent2:8080")
result = await bridge.delegate("Refactor the authentication module")

The agentskills.io Standard

Many skills in the ecosystem follow the agentskills.io open standard, making them portable across Hermes, Claude Code, Cursor, Codex, and others.

Installing agentskills.io Skills

# Cross-platform skills library
git clone https://github.com/wondelai/skills ~/.hermes/skills/wondelai

# Chainlink oracle skills (official)
git clone https://github.com/smartcontractkit/chainlink-agent-skills ~/.hermes/skills/chainlink

# FLUX image generation (official Black Forest Labs)
git clone https://github.com/black-forest-labs/skills ~/.hermes/skills/flux

# Pydantic AI type-safe skills
pip install pydantic-ai-skills

Writing an agentskills.io-Compliant Skill

# skill.py — agentskills.io compliant
from agentskills import skill, SkillInput, SkillOutput
from pydantic import BaseModel

class SearchInput(SkillInput):
    query: str
    max_results: int = 10

class SearchOutput(SkillOutput):
    results: list[dict]
    total: int

@skill(
    name="web-search",
    description="Search the web and return structured results",
    triggers=["search for", "look up", "find information about"],
)
async def web_search(input: SearchInput) -> SearchOutput:
    # implementation
    results = await do_search(input.query, input.max_results)
    return SearchOutput(results=results, total=len(results))

Common Patterns

Pattern: Skill Auto-Generation

Use

hermes-skill-factory
to create skills from repeated workflows:

git clone https://github.com/Romanescu11/hermes-skill-factory ~/.hermes/skills/skill-factory
hermes skills reload

# Now in chat:
# "Create a skill for the way I deploy to production"
# The agent observes your workflow and writes a skill for it

Pattern: SRE / Incident Response

# Install hermes-incident-commander
git clone https://github.com/Lethe044/hermes-incident-commander ~/.hermes/skills/incident

# In hermes.yaml — add monitoring cron
cron:
  tasks:
    - schedule: "*/5 * * * *"
      task: "check all production services for anomalies and alert if any are degraded"

Pattern: Weather + ML Pipeline

# Install weather plugin
git clone https://github.com/FahrenheitResearch/hermes-weather-plugin ~/.hermes/plugins/weather

# Usage in chat
# "Show me the NEXRAD radar for the last 6 hours over Chicago"
# "Build a training dataset from HRRR model data for last week"

Pattern: Literate Programming

pip install litprog-skill
hermes skills reload

# Now ask Hermes to write documented, executable notebooks
# "Write a literate program explaining this authentication module"

Self-Evolution Pipeline

For research/advanced use — evolve Hermes's own prompts using DSPy and GEPA:

git clone https://github.com/NousResearch/hermes-agent-self-evolution
cd hermes-agent-self-evolution
pip install -e .

# Run an evolution cycle
python evolve.py \
  --base-model openai/gpt-4o \
  --eval-suite ./evals/coding \
  --generations 10 \
  --output ./evolved-prompts

Troubleshooting

Skills Not Loading

# Check skill directories are configured
hermes config show | grep skills

# Validate a specific skill file
hermes skills validate ./my-skill/SKILL.md

# Force reload all skills
hermes skills reload --force

# Check skill logs
hermes logs --filter skills

Memory / Context Issues

# Check memory backend status
hermes memory status

# Compact/vacuum SQLite memory store
hermes memory compact

# Export memory for debugging
hermes memory export --output memory-dump.json

# Clear a specific session
hermes memory clear --session SESSION_ID

Messaging Gateway Not Receiving Messages

# Test Telegram connectivity
hermes gateway test telegram

# Check webhook status
hermes gateway status

# Re-register webhook
hermes gateway restart telegram

MCP Server Connection Failures

# List MCP servers and their status
hermes mcp list

# Test a specific MCP server
hermes mcp test filesystem

# View MCP server logs
hermes logs --filter mcp --server filesystem

Agent Loops / Hangs

# Set a max turn limit
hermes chat --max-turns 20

# Enable verbose mode to see what's happening
hermes chat --verbose

# Kill a runaway agent process
hermes status       # find the session ID
hermes kill SESSION_ID

Key Resources

ResourceURL
Official Docshttps://hermes-agent.nousresearch.com/docs/
Core Repohttps://github.com/NousResearch/hermes-agent
Skills Standardhttps://agentskills.io
Discord Communityhttps://discord.gg/NousResearch
Community Skillshttps://github.com/wondelai/skills
Cybersecurity Skillshttps://github.com/mukul975/Anthropic-Cybersecurity-Skills
GUI Dashboardhttps://github.com/builderz-labs/mission-control
Self-Evolutionhttps://github.com/NousResearch/hermes-agent-self-evolution