dream

name dream description Consolidates stored memories by merging duplicates, resolving contradictions, and pruning stale entries. Use when memory count is high, search results feel noisy or repetitive, or periodic cleanup is needed to maintain memory quality. Mem0 Dream — Memory Consolidation This skill performs a memory consolidation pass: it fetches all project memories, identifies near-duplicates, flags contradictions, and prunes stale entries based on configured retention policies. All proposed changes are shown as a diff for user approval before anything is modified. IMPORTANT: Execute steps strictly in order (1 → 2 → 3 → 4 → 5 → 6). Each step depends on the previous one. Do NOT run steps in parallel or skip ahead. Step 1: Load Retention Policies Determine the active retention policy by running the parser script. Use the appropriate PLUGIN_ROOT variable for the current platform ( ${CLAUDE_PLUGIN_ROOT} , ${CODEX_PLUGIN_ROOT} , or ${CURSOR_PLUGIN_ROOT} ): python3 "<PLUGIN_ROOT>/scripts/parse_mem0_config.py" "<cwd>" Parse the JSON output (a dict of category → days | null ). If the script fails or returns {} , fall back to these built-in defaults: metadata.type Default retention session_state 90 days compact_summary 90 days all others no pruning Store the resolved policies for use in Step 3. Step 2: Fetch ALL Project Memories Call get_memories to retrieve every memory for the active project: get_memories( filters={ "AND" : [{ "user_id" : "<active_user_id>" }, { "app_id" : "<active_project_id>" }]}, page_size= 200 , ) If the response indicates more pages exist, paginate until all memories are fetched. Collect the full list before proceeding. If zero memories are found, print: No memories found for project <project_id>. Nothing to consolidate. …and stop. Step 3: Analyze — Find Issues Work entirely in-memory; do not modify anything yet. Group memories by metadata.type (use "unknown" when the field is absent). For each group, identify the following: 3a. Near-duplicate pairs (merge candidates) Two memories are near-duplicates when they express the same fact or decision but phrased differently (e.g., "Use PostgreSQL for auth" and "Auth DB is PostgreSQL"). Heuristics — two memories are near-duplicates if all of these hold: Similarity threshold: estimated cosine similarity > 0.9 (use noun/keyword overlap as proxy — if >60% of significant nouns overlap, treat as >0.9 similarity). Same metadata.type . Neither memory is pinned ( metadata.pinned != true ). For each qualifying pair, draft a merged version that is more complete and specific than either original. 3b. Contradictions Two memories contradict when they assert opposing facts about the same topic (e.g., "Deploy to ECS" vs. "Deploy to Vercel"). Identify the likely winner: the more recent memory with higher confidence wins. Store both IDs and their content for user review. 3c. Prune candidates A memory is a prune candidate when any of the following is true: Its metadata.type has a retention policy and the memory is older than the configured number of days (compare created_at to today). Its confidence score is below 0.3 AND it contains no information unique to this project (no file paths, identifiers, or domain-specific nouns). Always skip memories where metadata.pinned == true , regardless of age or confidence. Step 4: Print Diff Report Print a structured diff to the terminal before making any changes. Use exactly this format: ## dream — consolidation report Merges (<N>): [mem0:<id1>] + [mem0:<id2>] → "<merged content, 100 chars>" Conflicts (<N>): [mem0:<idA>] vs [mem0:<idB>] — "<topic>" [A/B/skip] Prune (<N>): [mem0:<id>] — <type>, <age>d old Proposed: <N> merges, <N> prunes, <N> conflicts. Apply? [Y/n] If there are zero items in any category, omit that section entirely. If there are zero total proposals (no merges, no prunes, no conflicts), print: Dream complete. No duplicate, contradictory, or stale memories found. …and stop. Step 5: Wait for User Input and Apply 5a. Contradictions For each CONFLICT pair in the report, wait for the user to type A , B , or skip (case-insensitive). If they enter nothing (empty), treat as skip . Record the winner for each pair before proceeding to the final apply confirmation. 5b. Final confirmation After all conflict resolutions are collected, prompt: Apply? [Y/n] If the user types n or no (case-insensitive), print Cancelled. No changes made. and stop. If the user confirms ( Y , yes , or empty / Enter), apply all changes in this order: Merges For each approved merge pair: delete_memory(<id1>) delete_memory(<id2>) add_memory with: text="<merged content>" user_id=<active_user_id> app_id=<active_project_id> (top-level, not in metadata) metadata={"type": "<original type>", "branch": "<active_branch>", "confidence": <higher of the two original scores>, "source": "mem0-dream"} infer=False Contradictions (resolved) For each resolved conflict where the user chose A or B: Delete the loser (the non-chosen memory): delete_memory(memory_id=<loser_id>) Contradictions where the user chose skip are left untouched. Prunes For each prune candidate: delete_memory(<memory_id>) Step 6: Print Summary After all changes are applied, print: Dream complete — merged: <N>, pruned: <N>, conflicts resolved: <N>, skipped: <N> Auto mode When invoked with --auto (e.g., /mem0:dream --auto ), run non-interactively: Merges : applied automatically (no contradiction, both are compatible). Prunes : applied automatically (age/confidence-based, no ambiguity). Contradictions : skipped — they require human judgment. Concurrency guard Before doing any work, check for a lock file at /tmp/mem0_dream_auto.lock : If the lock file exists and is less than 10 minutes old, print [mem0-dream --auto] Another run in progress — skipping. and stop. Otherwise, create the lock file (write the current timestamp). Delete it when done (in all exit paths). Execution In auto mode: Load policies and fetch memories (Steps 1–3) as normal. Apply merges and prunes silently without printing the diff or prompting. Print a compact summary: [mem0-dream --auto] project=<id> merged=<N> pruned=<N> conflicts_skipped=<N> If contradictions were detected but skipped, check if a mem0-dream-auto reminder already exists before storing one: Search for existing reminders: search_memories(query="mem0-dream contradictions manual review", filters={"AND": [{"user_id": "<active_user_id>"}, {"app_id": "<active_project_id>"}, {"metadata": {"source": "mem0-dream-auto"}}]}, top_k=1) If a result exists with similarity > 0.9, skip storing the reminder (one already exists). If no match, store the reminder: add_memory( text= "mem0-dream detected <N> contradiction(s) requiring manual review. Run /mem0:dream to resolve them interactively." , user_id= "<active_user_id>" , app_id= "<active_project_id>" , metadata={ "type" : "task_learning" , "source" : "mem0-dream-auto" , "branch" : "<active_branch>" }, infer= False , ) See also /mem0:forget — targeted deletion of specific memories (search + confirm + delete) /mem0:health --deep — quick quality scan without applying changes