Weekly Reflect

${var} — Area to focus on. If empty, reviews everything.

If ${var} is set, focus the reflection on that specific area.

Today is ${today}. Your task is to review the agent's recent activity and maintain long-term memory.

Steps:

1. Read memory/MEMORY.md to understand current memory state.
2. Read the recent run logs in memory/logs/ (last 7 days if available).
3. Read the recent articles in articles/ (last 7 days if available).
4. Consolidate what you've learned:
   • What topics have been covered recently? Note any patterns or gaps.
   • What features were built? Record key decisions and outcomes.
   • Are there any stale entries in MEMORY.md that are no longer relevant? Remove them.
   • Are there recurring errors or issues worth noting for future runs?
   • Check memory/skill-health/*.json for quality trends — note any skills with declining scores or persistent flags. Summarize overall skill health in the appropriate topic file.
5. Reorganize memory:
   • Keep MEMORY.md as a short index (~50 lines): goals, active topics, and pointers to topic files.
   • Move detailed notes into memory/topics/ files (e.g. crypto.md, research.md, projects.md).
   • If a topic file already exists, update it rather than creating a new one.
6. Log what you did to memory/logs/${today}.md.
7. Send a notification via ./notify: "Memory consolidated — ${today}"

Be ruthless about pruning. Memory should be a living, useful document — not an append-only log.