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fix(memory): close the content gap so agents can actually write and retrieve learnings
- run-selected-prompt.mjs: set SCHEDULER_MEMORY_FILE env var before spawning each agent so store.mjs has a well-known path to read from (memory-updates/<ts>__<agent>.md) - retrieve.mjs: format memories.md using m.summary + date/tags in readable markdown sections instead of raw m.content blobs; agents can now scan injected context at a glance - store.mjs: remove semantically-empty fallback placeholder events that polluted the store and degraded retrieval quality; also fix default cadence 'weekly' -> 'daily' to match retrieve - scheduler-flow.md: replace vague "write insights" instruction with a concrete three-section template (Key findings / Patterns / Warnings) and clarify that $SCHEDULER_MEMORY_FILE is set by the scheduler automatically Co-Authored-By: Claude Sonnet 4.6 <[email protected]>
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@@ -38,7 +38,21 @@ Every agent prompt invoked by the schedulers (daily/weekly) MUST enforce this co
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- **Agent Action**: Review `.scheduler-memory/latest/<cadence>/memories.md` for relevant context.
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5. **Store memory after implementation and before completion publish**:
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- **Agent Action**: Write any new insights, learnings, or patterns to the file specified by `$SCHEDULER_MEMORY_FILE` (defaulting to `memory-updates/<timestamp>__<agent>.md`).
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- **Agent Action**: Write any new insights, learnings, or patterns to the file specified by `$SCHEDULER_MEMORY_FILE`. The scheduler sets this env var to `memory-updates/<timestamp>__<agent>.md` automatically — do not compute a path yourself.
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- **What to write** — use this template (keep each bullet to 1-2 lines; omit sections with nothing to say):
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```markdown
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# Memory Update — <agent-name> — <YYYY-MM-DD>
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## Key findings
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- <concrete fact discovered this run, e.g. "ESLint v9 requires flat config">
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## Patterns / reusable knowledge
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- <technique or pattern that will help this agent on its next run>
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## Warnings / gotchas
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- <env quirk, test failure, or constraint to watch for>
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```
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- Write only facts that will help the **same agent** on its **next run**. Skip meta-commentary about the task structure.
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- Run configured memory storage workflow after prompt execution (for example via `scheduler.memoryPolicyByCadence.<cadence>.storeCommand`)
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- Storage command MUST call real memory services (`src/services/memory/index.js#ingestEvents`, which uses ingestor/summarizer pipeline) and MUST emit deterministic marker `MEMORY_STORED`.
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- Storage command MUST ingest content from the file at `$SCHEDULER_MEMORY_FILE` (or fallback to `memory-update.md` if present).
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