Slash Command

/optimize-memory-bank

Scans .memory_bank/**/*.md files for redundancy, creates backup, optimizes files with >10% redundancy (target 30-50% reduction), and reports metrics summary.

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code-quality

performance

npx claudepluginhub mderk/memento --plugin memento

Prompt Preview

# Optimize Memory Bank for Redundancy

## Safety: Create Backup

**CRITICAL**: Before any changes:


Backup created at: `.memory_bank.backup.YYYYMMDD_HHMMSS`

## Optimization Process

1. **Load redundancy patterns ONCE** (reuse for all files):
   - Load common redundancy patterns and detection rules
   - Prepare optimization strategies for identified patterns

2. **Scan files**: Find all `.memory_bank/**/*.md` files using Glob

3. **For EACH file** (sequential, no subagents):

   a. **Read and analyze**:
      - Read file content
      - Count lines (before_lines)
      - Report: `🔍 Checki...

Command Content

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commands-team-collaboration

Stats

Parent Repo Stars21

Parent Repo Forks1

Last CommitMar 6, 2026

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# Optimize Memory Bank for Redundancy ## Safety: Create Backup **CRITICAL**: Before any changes: Backup created at: `.memory_bank.backup.YYYYMMDD_HHMMSS` ## Optimization Process 1. **Load redundancy patterns ONCE** (reuse for all files): - Load common redundancy patterns and detection rules - Prepare optimization strategies for identified patterns 2. **Scan files**: Find all `.memory_bank/**/*.md` files using Glob 3. **For EACH file** (sequential, no subagents): a. **Read and analyze**: - Read file content - Count lines (before_lines) - Report: `🔍 Checki...

Optimize Memory Bank for Redundancy

Safety: Create Backup

CRITICAL: Before any changes:

cp -r .memory_bank .memory_bank.backup.$(date +%Y%m%d_%H%M%S)

Backup created at: .memory_bank.backup.YYYYMMDD_HHMMSS

Optimization Process

Load redundancy patterns ONCE (reuse for all files):

Load common redundancy patterns and detection rules
Prepare optimization strategies for identified patterns

Scan files: Find all .memory_bank/**/*.md files using Glob

For EACH file (sequential, no subagents):

a. Read and analyze:

Read file content
Count lines (before_lines)
Report: 🔍 Checking [filename] (X lines)...

b. Check redundancy:

Apply redundancy pattern detection
Calculate redundancy percentage

c. Optimize if needed:

If redundancy >10%:
- Apply optimization fixes for detected patterns
- Preserve unique content (never lose information)
- Target: 30-50% reduction
- Overwrite file with optimized version
- Count new lines (after_lines)
- Calculate reduction: ((before - after) / before) * 100
- Report: ✅ Optimized [filename]: X → Y lines (-Z%)
If redundancy ≤10%:
- Keep original unchanged
- Report: ✅ [filename] already optimal

d. Track metrics: Add to running totals (files_optimized, total_lines_saved)

Final report: Show summary with before/after metrics

Expected Results

Typical outcomes:

30-50% reduction in verbose files

Preserved content quality

Improved consistency

Faster context loading

Report example:

✓ Scanned 28 files ✓ Optimized 12 files (43%) ✓ Saved 1,850 lines (38% average reduction) ✓ Backup: .memory_bank.backup.20251114_143022 Top improvements: - tech_stack.md: 648 → 301 lines (-54%) - ai-agent-handbook.md: 404 → 251 lines (-38%) - architecture.md: 520 → 310 lines (-40%)