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- Moved everything from ideas/passepartout/ to projects/passepartout/ - Moved legal structures to projects/flags/ - Created missing _index.org files for all subdirectories - Stripped redundant passepartout- prefix from filenames - Rewrote root _index.org as generalized brain index (projects + concepts) - Updated Hugo nav to Projects/Concepts - Updated build script section descriptions - Deleted stale ideas/passepartout-economics.md orphan
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Hermes Agent — Personal AI Assistant
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 competitive analysis for the landscape view and comparison.