TT-Wang/cortex-plugin

v0.9.3 Breaking

This release includes 2 breaking changes for platform teams planning a safe upgrade.

Published 1mo MCP Developer Tools

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✓ No known CVEs patched

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✓ No known CVEs patched in this version

Topics

anthropic claude-code claude-code-plugin local-first mcp mcp-server

+4 more

memory obsidian persistent-memory python

Summary

AI summary

Removed the staging layer and drift bug that left projects without playbooks when they had many memories.

Full changelog

Playbooks now derive directly from memories with a staleness hash. Fixes the drift bug where projects with many memories ended up with no playbook because the old staging layer only populated during active mining batches.

Changed

_playbook_refine(project) reads memories directly (no staging layer)
Source-hash gate: re-running with unchanged memories is a cheap no-op, no Haiku call
_playbook_sweep() refreshes every project with ≥5 memories in one pass — mining now calls this at end-of-batch, so no project is left behind due to batch gating
Minimum threshold of 5 memories before a playbook is written
--rebuild-playbooks now uses the sweep, with optional --force flag

Removed

_playbook_append and staging jsonl files — the staging layer that caused the drift bug

Migration

On the next mining batch (or python3 -m memem.server --rebuild-playbooks), the sweep rebuilds all drifted projects from current memories. Expect ~12 Haiku calls for a typical drifted install.

Breaking Changes

Removed `_playbook_append` function and staging JSONL files that implemented the staging layer
Playbooks now require a minimum of 5 memories before being written

View diff on GitHub

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About TT-Wang/cortex-plugin

Persistent, self-evolving memory plugin for Claude Code. Background miner extracts durable lessons (decisions, conventions, bug fixes)

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