haeres

Latin: heir, inheritor

Knowledge inheritance for AI agents. DNA for LLMs.

pip install haeres

The idea

Tasks execute and die. The knowledge they discover shouldn't die with them.

In biology, organisms are ephemeral but genes persist across generations. The same pattern applies to AI agents: each instance is temporary, but the knowledge it produces can outlive it — shaping how future instances think and act.

haeres is the mechanism of inheritance. A shared directory where agents leave knowledge for future agents to find. No server, no framework, no SDK. Just files.

Usage

Python

from haeres import post, read, clear

# A task discovers something — leave it for the next generation
post("KIID shows 0.42% TER but Morningstar shows 0.45%",
     sender="avantis-verify", to="finance-tasks", severity="action")

# Next generation reads what predecessors learned
msgs = read(to="finance-tasks")

# Knowledge consumed — clear it
clear(msgs[0]["id"])

CLI

haeres post "Found NAV discrepancy" --from avantis-verify --to terry -v action
haeres list --to terry
haeres clear 2026-03-20-1915-nav-discrepancy
haeres archive --all

MCP

haeres includes an MCP server, making it available as native tools for any MCP-connected LLM:

haeres-mcp  # starts the MCP server

Any agent, any platform

No SDK needed. Any agent that can read and write files can inherit:

cat > ~/notes/ACTA/2026-03-20-message.md << 'EOF'
---
from: my-skill
to: all
severity: info
ts: 2026-03-20T19:15+0800
---

Knowledge that should outlive this task.
EOF

Design principles

• Agents are commodity instances. Every LLM invocation is interchangeable.
• Skills are the identity. Knowledge comes from what you load, not who you are.
• Files are the communication layer. Durable, cross-platform, survives reboots.
• Async over sync. Like the endocrine system, not the nervous system.

Configuration

export ACTA_DIR=/path/to/shared/board  # default: ~/notes/ACTA

License

MIT