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Skill

hermes-dojo

by Yonkoo11

AI Summary

Hermes Dojo is your agent's training gym. It reads your past sessions, finds where the agent struggles, creates or improves skills to fix those weaknesses, and tracks improvement over time.

Install

Copy this and paste it into Claude Code, Cursor, or any AI assistant:

I want to install the "hermes-dojo" skill in my project.

Please run this command in my terminal:
# Install skill into your project
mkdir -p .claude/skills/hermes-dojo && curl --retry 3 --retry-delay 2 --retry-all-errors -o .claude/skills/hermes-dojo/SKILL.md "https://raw.githubusercontent.com/Yonkoo11/hermes-dojo/master/SKILL.md"

Then restart Claude Code (or reload the window in Cursor) so the skill is picked up.

Description

Continuous self-improvement system for Hermes Agent. Analyzes your past sessions to find recurring failures and skill gaps, then automatically creates or patches skills and runs self-evolution to fix them. Set it to run overnight and wake up to a better agent. Use /dojo to start.

Overview

Hermes Dojo is your agent's training gym. It reads your past sessions, finds where the agent struggles, creates or improves skills to fix those weaknesses, and tracks improvement over time. The core loop: measure → identify weakness → fix → evolve → verify → report

Commands

• /dojo or /dojo analyze — Analyze recent sessions for failure patterns • /dojo improve — Fix the top weaknesses (patch skills + run self-evolution) • /dojo report — Show current performance metrics and improvement history • /dojo history — Show learning curve over time • /dojo auto — Set up overnight cron: analyze + improve + report at 6am • /dojo status — Quick summary of agent health

Step 1: Analyze

Run python3 ~/.hermes/skills/hermes-dojo/scripts/monitor.py to scan recent sessions. This reads ~/.hermes/state.db and produces a JSON report with: • Per-tool success/failure rates • Error patterns (grouped by tool and error type) • User correction signals (messages containing "no,", "wrong", "I meant", "not what I") • Skill gap detection (repeated manual tasks with no skill) • Session-level metrics (tool calls per session, retry patterns) Present the results as a clear dashboard: ` === Hermes Dojo Analysis === Sessions analyzed: 23 (last 7 days) Total tool calls: 156 Overall success rate: 78% Top Weaknesses: • terminal_run: 73% success (12 failures) — common error: "command not found" • web_extract: 81% success (4 failures) — common error: "timeout" • No skill for: CSV parsing (requested 4 times) User Corrections Detected: 7 • 3x wrong file path • 2x wrong command syntax • 2x misunderstood request `

Step 2: Improve

For each identified weakness, decide the fix: A) Existing skill fails → patch it: • Read the current skill's SKILL.md • Analyze the failure patterns from Step 1 • Use skill_manage with action "patch" to add error handling, better instructions, or edge case coverage • Log the change B) No skill exists for a recurring need → create one: • Analyze the session patterns where this capability was needed • Use skill_manage with action "create" to make a new skill • Include specific instructions based on what worked in past sessions • Log the creation C) Skill exists but needs deeper improvement → run self-evolution: • Run: cd ~/.hermes/hermes-agent-self-evolution && .venv/bin/python3 -m evolution.skills.evolve_skill --skill <name> --hermes-repo ~/.hermes --iterations 5 --eval-source synthetic • This uses GEPA to analyze execution traces and propose targeted improvements • Review the evolution output — accept if score improved • Log before/after scores

Discussion

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Health Signals

MaintenanceCommitted 2mo ago
Active
Adoption100+ stars on GitHub
138 ★ · Growing
DocsREADME + description
Well-documented

GitHub Signals

Stars138
Forks14
Issues0
Updated2mo ago
View on GitHub
MIT License

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Works With

Claude Code