🧠 Agent Memory Optimizer
Version: 1.0.0 | Price: $3.99 | Author: Peru 🇵🇪
Description
Analyzes an AI agent's memory files (MEMORY.md, memory/*.md), detects duplicates, stale information, missing indexes, and structural issues. Generates an optimization report with specific recommendations and can auto-fix common issues.
Features
- •Duplicate Detection — Fuzzy matching to find repeated information across files
- •Staleness Analysis — Identifies outdated dates, metrics, and references
- •Structure Audit — Checks heading hierarchy, link integrity, section organization
- •Memory Efficiency Score — 0-100 rating of memory health
- •Auto-Fix — Can automatically deduplicate, re-index, and reorganize
- •Detailed Reports — Markdown report with specific, actionable recommendations
Requirements
- •
python3(3.8+) - •Python packages:
difflib(stdlib),re(stdlib),pathlib(stdlib) - •No external dependencies! Uses only Python standard library.
Installation
Copy this skill folder to your workspace. No pip install needed.
bash
chmod +x analyze.py optimize.py
Usage
Analyze Memory
bash
# Analyze current workspace (auto-detects MEMORY.md and memory/ folder) python3 analyze.py # Analyze a specific directory python3 analyze.py --path /path/to/workspace # Output report to file python3 analyze.py --output report.md # JSON output python3 analyze.py --json
Apply Optimizations
bash
# Preview changes (dry run — default) python3 optimize.py # Apply all recommended fixes python3 optimize.py --apply # Apply only deduplication python3 optimize.py --apply --only dedup # Apply only re-indexing python3 optimize.py --apply --only reindex # Backup before applying python3 optimize.py --apply --backup
All Options
code
analyze.py [OPTIONS] --path DIR Workspace directory to analyze (default: current dir) --output FILE Save report to file --json Output as JSON --verbose Show detailed analysis --help Show help optimize.py [OPTIONS] --path DIR Workspace directory (default: current dir) --apply Apply fixes (default: dry run) --only TYPE Only apply: dedup, reindex, stale, structure --backup Create .bak files before modifying --help Show help
Output Format
Analysis Report
markdown
# 🧠 Memory Optimization Report Workspace: /root/.openclaw/workspace Analyzed: 2026-02-14 03:00 UTC ## Memory Efficiency Score: 72/100 ### Summary - Files scanned: 15 - Total entries: 234 - Duplicates found: 12 - Stale entries: 8 - Missing indexes: 3 - Structure issues: 5 ## 🔴 Critical Issues 1. **12 duplicate entries** across MEMORY.md and memory/2026-02-10.md - "GitHub token configured" appears 3 times - "TTS setup complete" appears 2 times ## 🟡 Warnings 1. **8 stale entries** with dates older than 30 days - memory/2025-12-15.md: "Current project: X" (60 days old) ## 🟢 Suggestions 1. Consider merging memory/2026-02-01.md through memory/2026-02-05.md (low activity) 2. Add table of contents to MEMORY.md (>50 entries) ## Recommended Actions - [ ] Remove 12 duplicate entries (saves ~2.4KB) - [ ] Archive 8 stale entries - [ ] Add index headers to 3 files - [ ] Fix 5 structural issues
How It Works
- •File Discovery — Scans for MEMORY.md, memory/*.md, and related files
- •Content Parsing — Extracts entries, headers, dates, metrics from markdown
- •Duplicate Detection — Uses SequenceMatcher for fuzzy matching (>80% similarity)
- •Staleness Check — Parses dates and flags entries older than configurable threshold
- •Structure Analysis — Validates heading hierarchy, checks for orphan sections
- •Scoring — Calculates efficiency score based on weighted issue counts
- •Report Generation — Compiles findings into actionable markdown report
Example
bash
$ python3 analyze.py --path /root/.openclaw/workspace 🧠 Agent Memory Optimizer v1.0.0 Scanning workspace: /root/.openclaw/workspace Found 12 memory files (45.2 KB total) Analyzing... Memory Efficiency Score: 72/100 ⚠️ Issues found: 🔴 Critical: 2 🟡 Warning: 5 🟢 Suggestion: 3 Report saved to: memory_report.md Run `python3 optimize.py --apply` to fix issues.