memesh-review · diff
git:20260906.50bf239 to git:20260924.6aaf317
13 added, 34 removed. Audit A to A.
---
name: memesh-review
description: Review and optimize the MeMesh memory database. Analyzes health score, finds stale or noisy memories, shows work patterns, and suggests human-reviewed cleanup actions. Use when asked to "review memories", "check memory health", "clean up knowledge", or "what's in my memory".
user-invocable: true
---
# MeMesh Memory Review
Review the memory database and provide actionable cleanup recommendations.
## How to Access
Use CLI (works everywhere) or MCP tools (if available). See the `memesh` skill for auto-detect instructions.
## Process
### Step 1: Gather data
```bash
# Get system health
memesh status
# Get all recent memories (structured output for analysis)
memesh recall --limit 50 --json
- # Get memories by type for quality analysis
- memesh recall --tag "type:decision" --json
- memesh recall --tag "type:lesson_learned" --json
- memesh recall --tag "type:session_keypoint" --json
+ # `--tag` filters actual tags; inspect each returned entity's `type` to group decisions, lessons, and session records.
```
+ Recall is a bounded window, not a whole-database count. For an exact health
+ score and factor totals, use the Dashboard Analytics view after `memesh serve`
+ or its local `GET /v1/analytics` endpoint. If it is unavailable, omit the
+ score and label any counts from recall as sample counts.
+
If MCP `user_patterns` tool is available, also run it for work pattern analysis:
```json
user_patterns: {}
```
### Step 2: Analyze and report
- From the recalled data, compute and present:
+ Use the analytics result for graph-wide totals and health factors; use recalled
+ memories to illustrate findings. Present only fields you actually obtained:
```markdown
## Memory Health Report
### Overview
- Total entities: N
- Last 30 days active: N (N%)
- Knowledge types: N decisions, N patterns, N lessons, N auto-tracked
### Health Score: N/100
- - Activity: N% (accessed in last 30 days)
- - Quality: N% (high confidence, well-tagged)
- - Freshness: N% (new this week)
- - Self-Improvement: N% (lessons learned ratio)
+ - Activity: N/30 points (active entities accessed in the last 30 days / all active entities)
+ - Quality: N/30 points (active entities with confidence > 0.7 / all active entities)
+ - Freshness: N/20 points (entities created in the last 7 days / all active entities, capped at 1)
+ - Lessons: N/20 points (`lesson_learned` entity count / 5, capped at 1)
### Quality Issues Found
**Stale (not accessed 30+ days, low confidence)**
- "entity-name" — confidence: N% — Suggest: archive?
**Verbose (5+ observations)**
- "entity-name" (N observations) — note it; there is no one-entity compression
command. If useful knowledge is spread across episodic entries, an already
running agent can prepare one MCP `work_package` for human review.
**Potential conflicts**
- "entity-A" vs "entity-B" — inspect the text and recommend an explicit
`contradicts` or `supersedes` relation; MeMesh does not judge it automatically
**Noise ratio**
- N% auto-tracked (session_keypoint, commit) vs N% intentional knowledge
- If noise > 80%: recommend more deliberate `memesh remember` usage
### Recommended Actions
1. `memesh forget --name "old-design"` (superseded)
2. Ask the current agent to prepare one MCP `work_package`; then review the staged proposal
3. `memesh remember ...` (knowledge gap in [area])
```
### Step 3: Execute approved actions
Present the report first. Ask which actions to execute. Then run the commands:
```bash
memesh forget --name "outdated-entity"
# MCP work_package submits one proposal; then use dream show / accept / reject
memesh remember --name "missing-knowledge" --type decision --obs "..."
```
### Step 4: Verify
```bash
memesh recall --limit 5 --json # confirm changes took effect
```
- ## Documentation & Code Quality Checks
-
- **For comprehensive documentation synchronization and lint checks**, use:
- ```bash
- @sa:comprehensive-code-review
- ```
-
- This skill includes:
- - **Dim 17: Documentation Synchronization** — version consistency, API docs, architecture docs, feature docs, deprecated terms, breaking changes
- - **Dim 18: Code Style & Lint** — lint errors/warnings, security rules, disabled rules, style consistency
-
- **MeMesh-specific automation**:
- ```bash
- # Quick verification (memesh-specific checks)
- node scripts/check-doc-claims.mjs
- # Exit code 0 = all checks pass
-
- # Lint check
- npm run lint # 0 errors expected, ~83 warnings (technical debt)
- ```
-
- ---
-
## Tips
- Run every 1-2 weeks to keep memory healthy
- - Health score < 50 → too many stale or low-quality memories
+ - Health score < 50 → inspect the four factor scores before recommending a cause
- Noise > 80% → encourage deliberate `memesh remember` for decisions
- Dashboard available at: http://localhost:3737/dashboard (run `memesh serve` first)
- - **Before merge**: Run documentation sync checklist above to prevent drift