kartik-mem0
1daa7ece66
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 ${MEM0_PROJECT_ID:-unknown} to avoid
crash when identity resolution fails under set -u
Important fixes:
- I1: session_stats.py tracks recent_ids (memory IDs + timestamps) for
/mem0:forget undo support. Capped at 50 entries.
- I2: /mem0:health --deep mode adds memory quality analysis: duplicate
detection, stale entry scan, contradiction flags, orphan tagging
- I3: /mem0:stats ASCII histogram for category distribution with bar
chart, sorted by count descending
- I4: mem0-mcp skill documents access counter pattern: get_memory then
update_memory to track which memories are actually used
- I5: on_pre_commit.py reads COMMIT_EDITMSG first (current commit),
falls back to HEAD only if EDITMSG unavailable
Tests: 91 -> 94 (3 new for recent_ids tracking)
83 lines
2.5 KiB
Markdown
83 lines
2.5 KiB
Markdown
---
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name: mem0-stats
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description: >
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Show memory statistics for the current session and project lifetime.
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Combines local session counters with API-fetched totals.
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TRIGGER: user runs /mem0:stats, or asks "how many memories", "mem0 stats",
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"memory usage", "show memory count".
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---
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# Mem0 Stats
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Show session and lifetime memory statistics.
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## Execution
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### Step 1: Gather session stats
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Run the session stats reporter:
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```bash
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SCRIPT_DIR="${CLAUDE_PLUGIN_ROOT:-${CODEX_PLUGIN_ROOT:-${CURSOR_PLUGIN_ROOT:-}}}/scripts"
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python3 "$SCRIPT_DIR/session_stats.py" peek 2>/dev/null || echo "{}"
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```
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The `peek` command returns JSON without clearing the stats file (unlike `report`).
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If the script returns empty or errors, note "No session data available" and continue.
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### Step 2: Fetch lifetime stats from API
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Call `get_memories` with:
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- `user_id=<active_user_id>`
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- `app_id=<active_project_id>`
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- `page_size=100`
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Count the returned memories. Group them by:
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1. `categories[0]` (platform-assigned) — primary grouping
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2. `metadata.type` (agent-assigned) — secondary if no categories
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3. `created_at` date — for age analysis
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Also run a `search_memories` call with `query="project"`, `limit=1` to measure round-trip latency (time the call).
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### Step 3: Display
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Print a compact dashboard with an ASCII histogram for category distribution:
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```
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## mem0 Stats
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### This Session
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Memories written: <N>
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Searches run: <N>
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Categories touched: <list>
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### Project Lifetime (<project_id>)
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Total memories: <N>
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By category:
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decision ████████████████ 24
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convention ██████████░░░░░░ 15
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anti_pattern ████░░░░░░░░░░░░ 6
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task_learning ███░░░░░░░░░░░░░ 5
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user_preference ██░░░░░░░░░░░░░░ 3
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session_state █░░░░░░░░░░░░░░░ 2
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Oldest memory: <date>
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Newest memory: <date>
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### Health
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API latency: <N>ms
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User: <user_id>
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Project: <project_id>
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Branch: <branch>
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```
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**Histogram rules:**
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- Max bar width: 16 characters. Scale all bars relative to the highest count.
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- Use `█` for filled and `░` for empty. Right-align the count number.
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- Sort categories by count descending. Omit categories with 0 memories.
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- If only 1-2 categories exist, still show the histogram — it provides visual context.
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Skip any section with zero data.
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