memory-continuity/CHANGELOG.md

Changelog

v2.0.0 — 2026-03-15

Summary

Major architecture upgrade: from prompt-based skill to lifecycle plugin. State injection and extraction now happen automatically via OpenClaw hooks, making recovery model-agnostic and reliable across all providers.

Added

• index.js — plugin entry point with 5 lifecycle hooks
• openclaw.plugin.json — plugin manifest with configSchema
• Automated installer (scripts/post-install.sh) that handles copy + config + restart

Changed

• Architecture: skill (prompt-based) → plugin (hook-based)
• before_agent_start hook injects CURRENT_STATE.md into system context automatically
• agent_end hook auto-extracts working state from conversation
• before_compaction hook preserves state through context compression
• before_reset hook archives state before /new
• session_end hook ensures state file exists
• README fully rewritten for plugin architecture
• post-install.sh rewritten for plugin installation flow

Removed

• Dependency on model cooperation for state read/write
• Reliance on skillsSnapshot cache clearing

Validated

• Tested with MiniMax M2.5 and GPT-5.4 on OpenClaw 2026.3.12
• /new recovery: agent correctly surfaces recovered state
• Multi-turn state: conversation context (secrets, scheduled events) persists across resets

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v0.3.0-probe — 2026-03-13

Summary

Transition from skill-only to dual-form package (skill + lifecycle plugin probe).

Added

• plugin/lifecycle-prototype.ts
• references/phase2-hook-validation.md

Changed

• Repository direction clarified: primary path is lifecycle plugin
• ContextEngine documented as future option, not v1 default

Validated

• Startup continuity injection on resident subagents
• Hook wiring confirmed without read tool dependency

Known limitation

• Skill-based approach unreliable: models can ignore recovery instructions
• This limitation is resolved in v2.0.0 by moving to hooks