Skip to main content

Knowledge inheritance for AI agents. DNA for LLMs.

Project description

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.

Biology AI system
Genes Skills (persistent knowledge)
Organisms Tasks (executed, then gone)
Bodies Agents (commodity instances)
Heredity haeres
Natural selection Human review

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

haeres-0.1.0.tar.gz (6.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

haeres-0.1.0-py3-none-any.whl (7.8 kB view details)

Uploaded Python 3

File details

Details for the file haeres-0.1.0.tar.gz.

File metadata

  • Download URL: haeres-0.1.0.tar.gz
  • Upload date:
  • Size: 6.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for haeres-0.1.0.tar.gz
Algorithm Hash digest
SHA256 7391e1283f7076ec361fda2e9c03a25d91efe81eb43fad2c7383d5956a1625d6
MD5 7f9ab131c3079a6f2366af4925a3b82e
BLAKE2b-256 0e2dcd6b8c1ee73958544349fc8c65ca888cc035d4487b85d307495aae5cfed5

See more details on using hashes here.

File details

Details for the file haeres-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: haeres-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 7.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.12

File hashes

Hashes for haeres-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 c5816bdb346d916192bf09fc8bb9dbd1da22496e897c06bf0c0e5e91175bfd2e
MD5 e4ca56eede2d32b2c27b3bff08989674
BLAKE2b-256 99eb16b2b4946f057b36636da751f89928a91eb9296eb146b608924cdd394a76

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page