Critical fixes:
- C1: Pin/dream update_memory now reads content first via get_memory
before updating, preventing metadata-only calls that wipe content
- C2: SessionStart memory count uses GET /v3/memories/?page_size=1 for
real count from pagination envelope instead of search limit=100
- C3: on_task_completed.sh uses ${MEM0_PROJECT_ID:-unknown} to avoid
crash when identity resolution fails under set -u
Important fixes:
- I1: session_stats.py tracks recent_ids (memory IDs + timestamps) for
/mem0:forget undo support. Capped at 50 entries.
- I2: /mem0:health --deep mode adds memory quality analysis: duplicate
detection, stale entry scan, contradiction flags, orphan tagging
- I3: /mem0:stats ASCII histogram for category distribution with bar
chart, sorted by count descending
- I4: mem0-mcp skill documents access counter pattern: get_memory then
update_memory to track which memories are actually used
- I5: on_pre_commit.py reads COMMIT_EDITMSG first (current commit),
falls back to HEAD only if EDITMSG unavailable
Tests: 91 -> 94 (3 new for recent_ids tracking)
7.4 KiB
name, description
| name | description |
|---|---|
| mem0-dream | Memory consolidation pass. Fetches all project memories, finds near-duplicates, merges them, flags contradictions, prunes stale entries per retention policy. Outputs a diff for user approval before applying changes. TRIGGER: user runs /mem0:dream, or asks "consolidate memories", "clean up memories", "merge duplicate memories", "run dream". |
Mem0 Dream — Memory Consolidation
This skill performs a memory consolidation pass: it fetches all project memories, identifies near-duplicates, flags contradictions, and prunes stale entries based on configured retention policies. All proposed changes are shown as a diff for user approval before anything is modified.
Step 1: Load Retention Policies
Determine the active retention policy by running the parser script. Use the
appropriate PLUGIN_ROOT variable for the current platform (${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(
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:
- Significant noun/keyword overlap in the memory text.
- 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.typehas a retention policy and the memory is older than the configured number of days (comparecreated_atto 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 (item 15)
Print a structured diff to the terminal before making any changes. Use exactly this format:
## Dream — Memory Consolidation Report
### Merge proposals (<N> pairs)
MERGE [mem0:<id1>] + [mem0:<id2>] → NEW
- Original 1: "<content of memory 1, truncated to 120 chars>"
- Original 2: "<content of memory 2, truncated to 120 chars>"
- Merged: "<drafted merged content>"
### Contradictions (<N> pairs)
CONFLICT [mem0:<idA>] vs [mem0:<idB>]
- A: "<content>" (<created_at date>, confidence: <score>)
- B: "<content>" (<created_at date>, confidence: <score>)
Which is current? [A/B/skip]
### Prune candidates (<N> memories)
PRUNE [mem0:<id>] — <metadata.type>, <age>d old (policy: <policy_days>d)
---
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_memorywith:messages=[{"role": "user", "content": "<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:
- Identify the loser (the non-chosen memory).
- First call
get_memory(<loser_id>)to read its current text content. - Then call
update_memory(<loser_id>, data=<original_text_content>)to preserve the text while updating it. - Important:
update_memoryrequires thedata(text) parameter. A metadata-only call may error or wipe the content. Always read first, then update with the original text.
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> pairs → <N> new memories
Pruned: <N> memories deleted
Flagged: <N> contradictions resolved, <N> skipped
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.
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, store a reminder memory:
add_memory( messages=[{"role": "user", "content": "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, )
Note: Claude Code does not have native cron/scheduling. To run dream periodically,
use an external scheduler (cron, launchd) calling claude -p "/mem0:dream --auto",
or run it manually at the start of each week.