:PROPERTIES:
:ID:       c652688a-1ea0-487c-9222-00e954efe8a1
:CREATED:  [2026-05-22 Thu]
:END:
#+title: Hermes Agent — Personal AI Assistant
#+filetags: :passepartout:strategy:competitive:hermes:

The agent running this conversation. Python, ~17K core lines, MIT.

Architecture: Synchronous conversation loop with OpenAI-format messages. 60+ built-in tools. 109+ providers via pluggable transport layer. 15+ messaging platforms via gateway. MCP client (native, not bridge). Ink/React TUI as Node.js subprocess. Cron jobs, Kanban board, subagent delegation.

Safety model: Multi-layer but NOT a deterministic gate stack: message sanitization, Tirith binary scanner, command approval system, memory injection detection, secret/PII redaction, tool call guardrails, MCP security, context fencing. All heuristic or prompt-based — no structural type-level gates.

Data model: SQLite session DB (FTS5 full-text search). File-based memory (MEMORY.md + USER.md). YAML config. No knowledge graph. No Org-mode.

Self-modification: Skill system writes SKILL.md files. Memory tool edits MEMORY.md/USER.md. Core Python code is read-only in execution but no gate specifically prevents the LLM from requesting source modifications.

Verification: None.

Key gap vs Passepartout: No deterministic gate stack (heuristic layers, not structural/typed), no knowledge graph, no Org-mode, no neurosymbolic architecture, no self-verification, no proof system. Hermes's strength is breadth — 109 providers, 15 platforms, MCP ecosystem. But it has no depth in safety, knowledge representation, or reasoning architecture.

See the full [[id:3aa22300-2f25-57b0-8787-9f199cc978b1][competitive analysis]] for the landscape view and comparison.