Memory Defragmentation
SkillFiles & storageDecomposes and reorganizes agent memory files into focused, single-purpose components. Use when memory has large multi-topic blocks, redundancy, or poor organization. Trigger phrases: "defrag memory", "reorganize memory", "clean up memory files", "split memory blocks".
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Memory Defragmentation skill
What this skill tells your AI
The instructions your AI receives, as published by edmundmiller/dotfiles in packages/pi-packages/pi-context-repo/skills/defragmenting-memory/SKILL.md and read by ahel’s review.
Requires context-repo extension with memory at
.pi/memory/
Splits large, multi-purpose memory blocks into focused single-purpose files
with hierarchical / naming.
When to Use
- Memory blocks have redundant information
- Files mix multiple unrelated topics
- Memory lacks structure (walls of text)
- After major project milestones
- Every 50-100 conversation turns
Workflow
Step 1: Backup (MANDATORY)
Use the memory_backup tool before proceeding. This is your safety net.
Step 2: Analyze Current Memory
find .pi/memory -name '*.md' | while read f; do
echo "=== $f ($(wc -l < "$f") lines) ==="
head -5 "$f"
echo
done
For each file, determine:
- Does it serve 2+ distinct purposes? → needs splitting
- Is it >40 lines? → candidate for splitting
- Does it overlap with another file? → consolidate
Step 3: Decompose
Split multi-purpose blocks into focused files using hierarchical naming:
Before:
system/project.md (80 lines mixing overview, tooling, conventions, gotchas)
After:
system/project/overview.md
system/project/tooling.md
system/project/conventions.md
system/project/gotchas.md
Use memory_write for each new file, then delete the original:
rm .pi/memory/system/project.md
Step 4: Clean Up
For each file (new and existing):
- Add markdown structure (headers, bullets)
- Remove redundancy across files
- Remove speculation ("probably", "maybe")
- Keep only actionable, concrete information
- Resolve contradictions
Step 5: Commit
memory_commit({ message: "refactor: defragment memory — split N files into M focused blocks" })
Step 6: Report
Provide a summary:
- Files created (new decomposed blocks)
- Files modified (what changed)
- Files deleted (if any, explain why)
- Before/after file counts and line counts
Evaluation Criteria
- DECOMPOSITION — Each file has ONE clear purpose described by its filename
- STRUCTURE — Headers, bullets, scannable at a glance
- CONCISENESS — No redundancy, no speculation, only unique value
- CLARITY — Contradictions resolved, plain language, actionable
- ORGANIZATION — General to specific within files, important first
Naming Rules
- Use
/hierarchy:project/tooling/testing.md(notproject-tooling-testing.md) - 2-3 levels of nesting
- ~40 lines max per file
- Descriptive frontmatter descriptions
What to Preserve
- User preferences (sacred — never delete)
- Project conventions discovered through experience
- Important context for future sessions
- Learnings from past mistakes
Rollback
If something goes wrong:
/memory-backups # list available backups
/memory-restore <backup-name>
Signals
- GitHub stars
- 80
- Forks
- 6
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
defragmenting-memory- Source
- github.com/edmundmiller/dotfiles