Skip to main content

Decision memory and session logging for AI-assisted development - track architectural decisions across sessions

Project description

memory-trail

Decision memory and session logging for AI-assisted development — track architectural decisions across sessions.

PyPI version License: CC BY 4.0

Status: Coming Soon

This package is part of the Clarity Gate ecosystem for epistemic quality verification.

Functionality is under development.

What Will This Do?

memory-trail will help you maintain continuity across AI-assisted development sessions:

  • Decision Memory: Track why architectural choices were made
  • Session Logging: Maintain context across conversation boundaries
  • Confidence Protocols: Document certainty levels for decisions
  • Agent Coordination: Share context between different AI agents

Use Cases

  • Track decisions made during multi-session development projects
  • Maintain "why" documentation alongside "what" documentation
  • Coordinate context between Claude, Copilot, and other AI assistants
  • Create audit trails for AI-assisted architectural decisions

Related Packages

License

CC BY 4.0 — Use freely with attribution.

Author

Francesco Marinoni Moretto
GitHub: @frmoretto

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

memory_trail-0.0.1.tar.gz (2.3 kB view details)

Uploaded Source

Built Distribution

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

memory_trail-0.0.1-py3-none-any.whl (3.1 kB view details)

Uploaded Python 3

File details

Details for the file memory_trail-0.0.1.tar.gz.

File metadata

  • Download URL: memory_trail-0.0.1.tar.gz
  • Upload date:
  • Size: 2.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.2

File hashes

Hashes for memory_trail-0.0.1.tar.gz
Algorithm Hash digest
SHA256 182a77d02928f610fc86f4961563426b7cc2035eb3ba0800a389cac74d9003c7
MD5 1684760dcf1187034ee1852de081b174
BLAKE2b-256 347bc0421954f0a238df2e3a705733f9f8460f620fe5a5759934bf7e96bfcc7e

See more details on using hashes here.

File details

Details for the file memory_trail-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: memory_trail-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 3.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.2

File hashes

Hashes for memory_trail-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 65a594465af7db4ad4a2a86c1afaea8dcf17f7fa29a656d0ebd6d2b639a988dc
MD5 c8c40d24133f9314b460b97f8caf94b7
BLAKE2b-256 537692a4699b32381afb2266db478912331f9d8b094c10a4c174b602960ee9ba

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