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Hermes Agent — Core Skill Setup Guide

Source: nousresearch/hermes-agent (Official) Skill: hermes-agent · Installs: 400+ · Category: Core / Agent Framework Platform: Linux, macOS, Windows

The official Hermes Agent core skill from Nous Research. Bundles the essential capabilities every Hermes agent needs: CLI invocation patterns, subagent delegation (delegate_task), persistent memory (FTS5 + LLM summaries), self-improving skills that auto-create from completed tasks, MCP bidirectional integration, browser automation, code execution, and web research.

Installation

# Install via skills.sh
npx skills add nousresearch/hermes-agent --skill hermes-agent -g -y

# Or clone the full repo
git clone https://github.com/NousResearch/hermes-agent.git
# Skill is at: hermes-agent/skills/hermes-agent/SKILL.md

Prerequisites

Requirement Details
Hermes Agent v0.20.0+
Shell Access hermes CLI must be in PATH
API Keys At least one LLM provider configured in config.yaml

Core Capabilities

1. CLI Invocation

Run Hermes from any agent or script:

# One-shot task execution
hermes run "Analyze this CSV file and generate a summary report"

# With specific model
hermes run --model claude-sonnet-4-6 "Review this PR diff"

# With skill pre-loading
hermes run --skill corpusiq-execution-discipline "Audit system health"

2. Subagent Delegation

Isolate complex subtasks into independent contexts:

# Delegate research task
hermes delegate "Research top 5 MCP server implementations and compare features"

# Parallel delegation (up to 3 concurrent)
hermes delegate --parallel \
  "Check X mentions" \
  "Scan Reddit for CorpusIQ threads" \
  "Review HN front page for relevant discussions"

Subagents get their own conversation, terminal session, and toolset. Results flow back as summaries — intermediate tool output never floods context.

3. Persistent Memory

Two-tier memory architecture:

  • FTS5 full-text search — fast keyword/boolean retrieval across all past sessions
  • LLM summaries — semantic compression of key facts, preferences, and patterns
# Search past sessions
hermes session search "MCP server deployment"

# Save durable facts
hermes memory add "Project uses PostgreSQL 17 with PGLite for dev"

4. Self-Improving Skills

Agents learn from completed tasks:

  • After complex tasks (5+ tool calls), the agent proposes a new skill
  • Skills encode the workflow, pitfalls, and verification steps
  • Next time the task type appears, the agent loads the skill automatically
  • Quality improves over time without manual curation
# List available skills
hermes skills list

# Create a new skill from a completed task
hermes skills create --from-session latest

5. MCP Integration

Bidirectional Model Context Protocol:

  • Client: Connect to external MCP servers (53+ tools registered)
  • Server: Expose Hermes capabilities as MCP tools for other agents
# List connected MCP servers
hermes mcp list

# Test a connection
hermes mcp test <server-name>

6. Browser Automation

Built-in browser tools for web interaction:

  • Navigate, snapshot, click, type, scroll, vision analysis
  • Console inspection for JS errors
  • Screenshot capture with AI annotation

Common Patterns

Pattern: Research → Synthesize → Report

# 1. Delegate research (runs in background)
hermes delegate "Research competitor pricing for AI data connectors"

# 2. While research runs, prepare report template
hermes run "Create a competitive analysis report template"

# 3. When research completes, synthesize
hermes run "Merge research findings into the report template"

Pattern: Code Review Pipeline

# 1. Delegate deep code review
hermes delegate --skill github-code-review "Review PR #42 in corpusiq-docs"

# 2. Parallel: check for security issues
hermes delegate --skill security-audit "Audit PR #42 for vulnerabilities"

# 3. Merge findings
hermes run "Combine code review and security audit into unified PR feedback"

Pattern: Daily Operations

# Morning health check
hermes run --skill corpusiq-system-auditor "Run system health check"

# Midday social sweep
hermes run --skill corpusiq-organic-discovery "Check all platforms for mentions"

# Evening report
hermes run --skill corpusiq-daily-html-reporting "Generate daily report"

Cost Awareness

Task Type Estimated Cost
Simple Q&A (single turn) $0.001–0.01
Research task (multi-turn) $0.02–0.10
Complex task with subagents $0.05–0.50
Full daily operations sweep $0.10–1.00

Costs vary by model selection. Sonnet is the cost-efficient default. Opus reserved for deep research and complex architecture.