61 lines
2.4 KiB
Markdown
61 lines
2.4 KiB
Markdown
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# SYS_20 — Agent Memory Protocol
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## Purpose
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Defines how agents read and write shared knowledge across the company.
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## Memory Layers
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### Layer 1: Company Memory (Shared, Read-Only)
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**Location:** `atomizer-protocols` and `atomizer-company` skills
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**Access:** All agents read. Manager proposes updates → Antoine approves.
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**Contains:** Protocols, company identity, LAC critical lessons.
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### Layer 2: Agent Memory (Per-Agent, Read-Write)
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**Location:** Each agent's `MEMORY.md` and `memory/` directory
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**Access:** Each agent owns their memory. Auditor can read others (for audits).
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**Contains:**
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- `MEMORY.md` — Long-term role knowledge, lessons, patterns
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- `memory/<project>.md` — Per-project working notes
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- `memory/YYYY-MM-DD.md` — Daily activity log
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### Layer 3: Project Knowledge (Shared, via Repo)
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**Location:** `/repos/Atomizer/knowledge_base/projects/<project>/`
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**Access:** All agents read. Manager coordinates writes.
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**Contains:**
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- `CONTEXT.md` — Project briefing (parameters, objectives, constraints)
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- `decisions.md` — Key decisions made during the project
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- `model-knowledge.md` — CAD/FEM details from KB Agent
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## Rules
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### Writing Memory
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1. **Write immediately** — don't wait until end of session
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2. **Write in your own workspace** — never modify another agent's files
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3. **Daily logs are raw** — `memory/YYYY-MM-DD.md` captures what happened
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4. **MEMORY.md is curated** — distill lessons from daily logs periodically
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### Reading Memory
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1. **Start every session** by reading MEMORY.md + recent daily logs
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2. **Before starting a project**, read the project's CONTEXT.md
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3. **Before making technical decisions**, check LAC_CRITICAL.md
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### Sharing Knowledge
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When an agent discovers something the company should know:
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1. Write it to your own MEMORY.md first
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2. Flag it to Manager: "New insight worth sharing: [summary]"
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3. Manager reviews and decides whether to promote to company knowledge
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4. If promoted: Manager directs update to shared skills or knowledge_base/
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### What to Remember
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- Technical decisions and their reasoning
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- Things that went wrong and why
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- Things that worked well
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- Client preferences and patterns
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- Solver quirks and workarounds
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- Algorithm performance on different problem types
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### What NOT to Store
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- API keys, passwords, tokens
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- Client confidential data (store only what's needed for the work)
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- Raw FEA output files (too large — store summaries and key metrics)
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