2026-02-20T11-14-26_auto_memory/debug.log, memory/MEMORY.md

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Nicholai Vogel 2026-02-20 04:14:26 -07:00
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<!-- generated 2026-02-19 04:02 -->
<!-- generated 2026-02-20 04:14 -->
Current Context
Focusing on repository migration compliance, system refactoring, and template consistency across the signetai and imessage-viewer projects.
Implementing Phase B: Shadow Extraction for the Signet memory pipeline. The focus is building the extraction and decision intelligence layer in shadow mode to validate quality/reliability without destructive consequences.
Active Projects
Apache 2.0 License Migration (`signetai` repo)
Status: Script creation in progress/verification needed.
Task: Migrate monorepo from MIT to Apache 2.0. Uses `git filter-repo` to rewrite only license files while preserving git history. Must also update NPM metadata.
iMessage Viewer Sync Refactor (`imessage-viewer` repo)
Status: Completed.
Details: Rewrote `lib/sync/ssh-pull.ts` to replace SSH+bash+tar approach with direct `rsync` calls (`rsync -az`). Deleted `scripts/remote-collect.sh`. Supports file-based sources (safari, chrome, shell) and directory sources (notes, reminders, calendar, contacts).
Signetai Skill Templates (`signetai` repo)
Status: Completed.
Details: Fixed `packages/signetai/templates/skills/recall/SKILL.md` and `packages/signetai/templates/skills/remember/SKILL.md` to use `signet recall/remember` CLI commands (e.g., `/api/memory/remember`) instead of outdated hook commands. Verified CLI functionality.
Phase B: Shadow Extraction Implementation
- Location: `packages/daemon/src/`
- Status: Planning complete, awaiting implementation
- Dependencies: Phase A infrastructure (schema migrations, DB accessor, feature flags) now in `c1e43b6`
- Next Steps:
1. Create `src/extract/` module with `extractFactsAndEntities(input): ExtractionResult`
2. Build `src/decision/` module for shadow candidate retrieval
3. Implement `src/worker.ts` with job queue processing (reads from `memory_jobs`, writes to `memory_history`)
4. Add contract validation and warning persistence
- Key Constraints:
- Extract from daemon.ts recall logic and hooks.ts extraction
- Keep semantics non-mutating
- All logs go to `memory_history` table only
- New files needed (daemon.ts is 4511 LOC)
Recent Work
Rsync-based Sync Implementation: Successfully refactored the sync mechanism in `imessage-viewer` to use direct `rsync` SSH connections, eliminating the need for a temporary bash script (`scripts/remote-collect.sh`) and minimizing forensic traces on the macOS system.
Skill Template Updates: Updated template files in the signetai repo to align with CLI commands, ensuring consistency for new installations.
License Migration Planning: Set up the plan to use `git filter-repo` for the signetai repository migration.
Phase A: Infrastructure Hardening (completed in `c1e43b6`)
- Schema migrations 001+002 for job queue/history tables
- Singleton DB accessor with WAL mode and read pool
- Transaction boundaries keeping provider calls outside write locks
- Content-hash dedup implementation
- Feature flags with kill switches (`PipelineV2Config`)
- Entity graph schema with proper entity types
- 102 tests passing
Team Structure Established
- Parallel agent delegation used successfully
- Schema-agent, db-accessor-agent, config-test-agent working in sequence
- Integration pass handling remaining wiring
Technical Notes
Git Tools: `git filter-repo` is being utilized for the license migration. It allows rewriting file contents without corrupting git history or authorship metadata.
Rsync Flags: Using `-az` (archive mode with compression) for the iMessage sync refactor.
Signet Architecture: Skills are located in `~/.agents/skills/`. CLI commands should target the installed CLI skills rather than API hooks for recall/remember actions.
Bun Runtime: Dashboard skills installer fix involves replacing `execSync("which bunx")` with `Bun.which()`.
Database Schema:
- `memory_jobs` table: stores job queue entries
- `memory_history` table: stores shadow extraction logs/proposals
- Feature flags: `PIPELINE_FLAGS` in `memory-config.ts`
Key Interfaces:
- `ExtractionResult`: structured facts + entities output
- `DecisionEngine`: retrieve top-K candidates, confidence scoring
- `SignetLifecycle` connectors pattern maintained
Tooling:
- Database access via singleton accessor
- Transaction wrappers for write operations
- Content hashing for deduplication
- Vector search integration for candidate retrieval
Code Standards:
- Self-explanatory code with "why" comments
- Max 700 LOC per file, max 3 indentation levels
- Test in browser (not lazy)
Rules & Warnings
File Locations: Skills and configuration files are located in `~/.agents/`, not `~/.local/share` or other standard locations.
Forensic Footprint: When running remote scripts, prefer direct `rsync` calls over temporary bash scripts to minimize shell history and system logs.
Bun API: Always use `Bun.which()` instead of `execSync("which bunx")` when checking for binaries.
Design: Use the `frontend-design` skill when working on frontend components.
Voice Transcription: Voice message transcriptions are handled via `obsidian-ai`, configured to read from `~/Library/Mobile Documents/iCloud~md~obsidian/Documents/ai-transcripts`.
Signet CLI: `/recall` and `/remember` skills should invoke the `signet recall` and `signet remember` CLI commands, not the `/api/hook/...` endpoints.
- Never delegate UI work to subagents (handle personally as Opus)
- Prefer Sonnet/Haiku delegation when operating as Opus
- Keep journal entries in memory database regularly
- Signet agent profile at `~/.agents/`
- Phase B work must be in new files (daemon.ts too large at 4511 LOC)
- Test in browser, don't be lazy
- Non-mutating semantics for shadow extraction phase

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@ -693,3 +693,5 @@ We are synthesizing a WORKING MEMORY document for Nicholai. Focus is on CURRENT
2026-02-20T04:14:05.513548 [regenerate] starting regeneration
2026-02-20T04:14:07.643865 [regenerate] found 477 transcripts, 50 memories
2026-02-20T04:14:07.643984 [regenerate] trying model: glm-4.7-flash
2026-02-20T04:14:21.259286 [regenerate] success with glm-4.7-flash (2737 chars)
2026-02-20T04:14:21.259448 [regenerate] wrote 2774 chars to MEMORY.md