The session loop that makes agentmemory pay off, recall before starting work, save at decision points, learn from corrections. Use when starting a nontrivial ta
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Memory only pays off when reads happen before the work and writes happen at decision points. This loop is the skill; every tool call in it is mechanical.
memory_smart_search { "query": "auth refresh flow", "project": "myrepo", "limit": 5 }
at task start, then at each settled decision:
memory_save { "content": "Chose cursor pagination over offset; offset scans broke past 100k rows in db/list.ts.", "concepts": "cursor-pagination, offset-scan-limit", "files": "src/db/list.ts" }
Hooks capture what happened automatically. What they cannot capture is judgment: which fact mattered, which decision was settled, which correction should change future behavior. That judgment applied at the right moments is this discipline.
memory_smart_search with the task topic and the project name. Spend the first tool call here; a hit saves rediscovery, a miss costs one call.memory_save with the decision AND the reason, 2-5 specific concepts, real file paths. Save at the moment of resolution; end-of-session batch saves lose the reasons.lesson skill). Lessons carry confidence and resurface before similar work; memories carry facts.memory_lesson_recall with the task type as query.Save: settled decisions with reasons, non-obvious constraints discovered by debugging, environment facts not derivable from the repo. Skip: anything readable from the code, transient state, secrets, and step-by-step narration (hooks already captured it).
WRONG: finish implementing, then search memory to double-check, and batch-save a summary of everything done.
RIGHT: search first, save each decision as it settles, let hooks own the summary.
recall, remember: the user-invoked forms of the read and write sides.lesson: the correction loop this discipline hands off to.See ../_shared/TROUBLESHOOTING.md if memory_smart_search or memory_save is not available.