fix(mem0-plugin): reduce memory noise, match openclaw storage pattern (#5229)
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Kartik
@@ -18,69 +18,47 @@ fi
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SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
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INPUT=$(cat)
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# Fire REST API transcript backup in background (safety net if agent
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# can't complete the add_memory call before compaction finishes)
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echo "$INPUT" | python3 "$SCRIPT_DIR/on_pre_compact.py" --source=pre-compaction 2>/dev/null &
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python3 "$SCRIPT_DIR/telemetry.py" pre_compact 2>/dev/null &
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cat <<'EOF'
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## CRITICAL: Pre-Compaction Session Summary
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## Pre-Compaction: Extract and store durable facts
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Context compaction is about to happen. You are about to lose most of your conversation history. You MUST store a comprehensive session summary NOW using the mem0 `add_memory` tool.
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Context compaction is about to happen. Review the conversation and store only facts that would help a future agent with ZERO context.
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### Step 1: Store session summary
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### What to store
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Call `add_memory` with `infer=False` and a thorough summary covering ALL of the following.
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For each fact, ask: "Would a new agent — with no prior context — benefit from knowing this?" If no, skip it. Most sessions produce 0-3 facts worth storing.
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`infer=False` is critical here: you've already done the extraction work yourself using full context. Without it, the platform runs a second LLM pass that loses your structure and pulls fragmented facts. With it, your summary is preserved verbatim.
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Store each fact as a SEPARATE `add_memory` call. One fact per call. 15-50 words each. Third person. Include file paths when relevant.
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```
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## Session Summary (Pre-Compaction)
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Categories and when to use them:
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- `decision` — architectural choices, trade-offs made ("Chose PostgreSQL over MongoDB for auth because of ACID requirements")
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- `task_learning` — patterns that worked ("Running migrations before seed in this repo avoids FK violations")
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- `anti_pattern` — approaches that failed ("Don't use batch insert for users table — triggers deadlock with audit log")
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- `convention` — coding standards discovered ("This repo uses snake_case for all Python files, camelCase for TS")
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- `user_preference` — how the user likes to work ("User prefers short PRs, one feature per branch")
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### User's Goal
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[What the user originally asked for and their intent]
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### What NOT to store
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### What Was Accomplished
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[Numbered list of tasks completed, features built, bugs fixed]
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- Session summaries or "what we did today" blobs
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- Raw file lists or command histories
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- Anything already stored in a prior `add_memory` this session
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- One-time information that won't recur
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- Transient state ("currently debugging X")
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### Key Decisions Made
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[Architectural choices, design decisions, trade-offs discussed]
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### How to store
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### Files Created or Modified
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[List of important file paths with what changed in each]
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### Current State
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[What is in progress RIGHT NOW — the task you were in the middle of]
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[Any pending items, blockers, or next steps]
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### Important Context
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[User preferences observed, coding patterns, anything that would help
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the post-compaction agent continue without asking redundant questions]
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```
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Tool call shape:
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```
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add_memory(
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messages=[{"role":"user","content":"<the summary above>"}],
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user_id="<the active user_id from the SessionStart bootstrap>",
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app_id="<the active project_id / app_id from SessionStart>",
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metadata={"type":"session_state","source":"pre-compaction","branch":"<active branch>"},
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messages=[{"role":"user","content":"<one fact, 15-50 words>"}],
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user_id="<active user_id>",
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app_id="<active project_id>",
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metadata={"type":"<category>","branch":"<active branch>","confidence":0.8},
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infer=False,
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)
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```
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### Step 2: Store any unstored learnings
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If there are learnings from this session that you haven't stored yet, store them as separate memories with `infer=False` (same reasoning -- you've already extracted the fact, don't re-extract):
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- Failed approaches -> metadata `{"type": "anti_pattern"}`
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- Successful strategies -> metadata `{"type": "task_learning"}`
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- Architecture decisions -> metadata `{"type": "decision"}`
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### Step 3: Acknowledge
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After storing, briefly tell the user that session state has been saved and you're ready for compaction.
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Do this NOW. Do not skip any section. The quality of this summary directly determines whether you can continue the user's task after compaction.
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If nothing durable happened this session, store nothing. That is correct.
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EOF
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exit 0
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