Hermes Agent Upgrade Plan — Mined from NotebookLM

Notebook: Hermes Agentic OS (31 sources)
Mined: 2026-07-13
Current model: glm-5.2 via ollama-cloud
Current config: /opt/data/config.yaml

TIER 1: High-Impact Config Optimizations (Apply Now)

1. Compression Tuning [ADVANCED]

Setting	Current	Recommended	Why
`compression.threshold`	0.5	0.75	Use 75% of context before compressing (vs 50%). Critical for reasoning tasks. Source [1,2]
`compression.target_ratio`	0.2	0.4	Keep 40% of conversation uncompressed after compression (vs 20%). Better task continuity. Source [1,2]
`tool_output.max_bytes`	50000	100000	Prevent truncation of long tool outputs (test logs, file reads). Source [1]
`tool_output.max_line_length`	2000	5000	Read long markdown paragraphs / minified files without missing content. Source [5]

2. Execution Limits & Safeguards [ADVANCED]

Setting	Current	Recommended	Why
`agent.max_turns`	150	60	Prevent token runaway when agent is stuck spinning. Source [6]
`tool_loop_guardrails.hard_stop_enabled`	false	true	Auto-terminate on repetitive tool-call patterns. Source [1,6]
`delegation.max_concurrent_children`	3	5	More parallel sub-agents for complex projects. Source [1] (token-heavy!)
`delegation.max_spawn_depth`	1	2	Allow sub-agents to spawn their own sub-agents for deep research. Source [1]

3. Auxiliary Model Cost Savings [ADVANCED]

Currently all auxiliary tasks use auto (falls back to main model = glm-5.2). Route background tasks to cheaper models:

auxiliary.vision → cheaper model for image analysis
auxiliary.compression → cheaper model for context summarization
auxiliary.curator → cheaper model for skill review/maintenance
auxiliary.skills_hub → cheaper model for skill searches
Cost savings: 3-5x on background tasks. Source [6,7]

4. Skill & Memory Safety [ADVANCED]

Setting	Current	Recommended	Why
`skills.guard_agent_created`	false	true	Scan agent-created skills for dangerous command patterns. Source [8]
`memory.write_approval`	(not set)	false (keep off for autonomous VPS)	Enable only if hallucinated facts become a problem. Source [4,7]

TIER 2: Automation & Cron Patterns to Implement

A. Dreaming Loop (Nightly Session Distillation) [ADVANCED]

The #1 most impactful pattern from the notebook. Distills daily sessions into a structured memory file.

hermes cron create "0 3 * * *" \
  --name "Dreaming" \
  --prompt "Review all sessions from today. Extract: 1) Decisions and reasoning 2) New projects, code changes, status 3) User-specific facts 4) Open tasks and next steps 5) Mistakes to avoid. Write structured summary to ~/.hermes/holme-profil.md. Focus on what I need to know tomorrow." \
  --deliver local

Source: Reddit r/hermesagent (HolmeBengt, Top 1% Poster)

B. GitHub Backup (Already Implemented ✅)

User already has GitHub backup workflow for hermes repo.

C. Morning Interview Pattern [BEGINNER]

Reverse-prompting pattern where Hermes interviews the user each morning:

Ask me: What are my priorities today? What tasks am I working on? What stresses me out? What's on my plate? Then categorize my tasks into: Autonomous (you handle), Review Required (show me), Too Risky (skip). Push autonomous tasks to the Kanban board.

Source: “100 hours of Hermes Agent lessons in 19 minutes” [24,25]

D. Kanban Librarian (Weekly Triage) [ADVANCED]

Flags tasks stuck in the same column for >7 days:

hermes cron create "0 9 * * 1" \
  --name "Kanban Librarian" \
  --prompt "Review all Kanban tasks. Flag any card stuck in the same column for more than 7 days. Move stale tasks to blocked status and notify me." \
  --deliver telegram

Source: “Every Level of Hermes Agent Explained” [5]

TIER 3: Multi-Agent & Orchestration Upgrades

A. Profile Architecture (The “Pantheon” Pattern) [ADVANCED]

Create specialized profiles for different roles:

# Mercury - cheap model for background crons/scraping
hermes profile create mercury --clone-from default
# Set mercury to use cheapest model (e.g., DeepSeek Flash or Gemini Flash)
 
# Labyrinth - high-reasoning for deep research
hermes profile create labyrinth --clone-from default
# Set labyrinth to use Claude Opus or equivalent

Source: “Hermes Agent just got 10X Better” [8,10,11]

B. Adversarial Loop (Builder/Verifier) [ADVANCED]

Use different models for building vs verifying:

Builder: Current model writes code/content
Verifier: Different model (e.g., GPT) reviews and critiques
Loop until verifier finds no issues Source: “Loop Engineering Totally 10x Hermes agents” [19-21]

C. /goal Command for Verifiable Outcomes [ADVANCED]

Set clear, verifiable end states instead of open-ended prompts:

/goal scrape YouTube to find the 50 highest-viewed videos about Hermes Agent and save transcripts as markdown files in the brain

The /goal feature keeps working until the verifiable outcome is achieved. Source: “How to Build AI Agents Better than 99% of People” [17,18]

TIER 4: Skills System Enhancements

A. Skill Bundles [ADVANCED]

Group frequently paired skills into a single slash command:

# ~/.hermes/skill-bundles/marketing.yaml
name: Marketing
skills:
  - ad-creative
  - ads-plan
  - copywriting
instruction: "Always research competitors before generating ad creative."

Then: /marketing loads all three skills at once.

B. Progressive Disclosure (Already Configured ✅)

tools.tool_search.enabled: auto — already set. This lazy-loads tool definitions.

C. Curator Configuration [ADVANCED]

Setting	Current	Recommended	Why
`curator.interval_hours`	168 (weekly)	72 (every 3 days)	More frequent skill maintenance
`curator.consolidate`	(not set)	true	Enable AI-powered skill consolidation (opt-in)

TIER 5: MCP & Integration Optimizations

A. MCP Idle Timeout for VPS RAM Recovery [ADVANCED]

For memory-heavy stdio servers (Playwright/Browser):

# Add to MCP server config
idle_timeout_seconds: 300  # Kill after 5 min inactivity, restart on next call

Source: “19 Hidden Features” [5]

B. Parallel Tool Calls for Read-Only MCP Servers [ADVANCED]

# For read-only servers (Google Search, Filesystem)
supports_parallel_tool_calls: true