Download skills/05-kthorn-research-superpower/research/cleaning-up-research-sessions/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does Cleaning Up Research Sessions live?
The publisher keeps it at https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.
Which agents can use Cleaning Up Research Sessions?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.
Safely remove intermediate files from completed research sessions while preserving important data
name: Cleaning Up Research Sessions
description: Safely remove intermediate files from completed research sessions while preserving important data
when_to_use: After research session is complete and consolidated. When research folder has accumulated temporary files. Before archiving or sharing research session.
version: 1.0.0
Cleaning Up Research Sessions
Overview
Remove intermediate files created during research workflow while preserving all important data.
Core principle: Conservative cleanup with user confirmation. Never delete anything important.
When to Use
Use this skill when:
Research session is complete and consolidated
Preparing to archive or share research session folder
Research folder has accumulated temporary/intermediate files
User explicitly asks to clean up
When NOT to use:
Research is still in progress
User hasn't reviewed final outputs yet
Unsure what files are safe to delete
Files That Are ALWAYS KEPT
NEVER delete these (protected list):
Core outputs:
SUMMARY.md - Enhanced findings with methodology
relevant-papers.json - Filtered relevant papers
papers-reviewed.json - Complete screening history
papers/ directory - All PDFs and supplementary files
abstracts-cache.json - Cached abstracts for re-screening (if exists)
rubric-changelog.md - Rubric version history (if exists)
Auxiliary documentation (if exists):
README.md - Project overview
TOP_PRIORITY_PAPERS.md - Curated priority list
evaluated-papers.json - Rich structured data
Project configuration:
.claude/ directory - Permissions and settings
*.py helper scripts that were created - Keep for reproducibility
Files That May Be Cleaned Up
Candidates for removal (with confirmation):
Intermediate search results:
initial-search-results.json - Raw PubMed results before screening
Safe to delete: Data is in papers-reviewed.json
Reason to keep: Shows raw search results for reproducibility
Temporary files:
*.tmp files
*.swp files (vim swap files)
.DS_Store (macOS)
__pycache__/ (Python cache)
*.pyc (Python compiled)
Log files:
*.log files
debug-*.txt files
Cleanup Workflow
Step 1: Analyze Research Session
cd research-sessions/YYYY-MM-DD-description/
# List all files with sizes
find . -type f -exec ls -lh {} \; | awk '{print $5, $9}' | sort -rh
Identify files by category:
Core outputs (MUST keep)
Methodology files (SHOULD keep)
Intermediate files (candidates for cleanup)
Temporary files (safe to delete)
Step 2: Present Cleanup Plan to User
Show what will be deleted:
🧹 Cleanup Analysis for: research-sessions/2025-10-11-btk-selectivity/
Files to KEEP (protected):
✅ SUMMARY.md (45 KB)
✅ relevant-papers.json (12 KB)
✅ papers-reviewed.json (28 KB)
✅ papers/ (14 PDFs, 32 MB)
✅ citations/citation-graph.json (5 KB)
✅ screening-criteria.json (2 KB)
✅ abstracts-cache.json (156 KB)
Files that CAN be removed (intermediate):
🗑️ initial-search-results.json (8 KB) - Raw PubMed results
🗑️ .DS_Store (6 KB) - macOS metadata
Total space to recover: 14 KB
Proceed with cleanup? (y/n/review)
Options:
y - Delete intermediate files
n - Cancel cleanup, keep everything
review - Show contents of each file before deciding
Step 3: Confirm Deletions
Before deleting ANY file:
Verify it's not in protected list
Check file isn't referenced in SUMMARY.md
Confirm with user one more time
Example confirmation:
About to delete:
- initial-search-results.json (8 KB)
This file contains raw PubMed search results. The data is preserved in
papers-reviewed.json, so this is safe to delete.
Confirm deletion? (y/n)
Step 4: Perform Cleanup
Delete confirmed files:
# Move to trash instead of rm (safer)
# On macOS:
mv initial-search-results.json ~/.Trash/
# On Linux:
mv initial-search-results.json ~/.local/share/Trash/files/
# Or use rm if user confirms
rm initial-search-results.json
Report results:
✅ Cleanup complete!
Removed:
- initial-search-results.json (8 KB)
- .DS_Store (6 KB)
Space recovered: 14 KB
Protected files preserved:
- All 8 core files kept
- All 14 PDFs kept
- All methodology documentation kept
✅ Integrity check passed
- All core files present
- All JSON files valid
- All PDFs intact
Special Cases
Case 1: Large abstracts-cache.json
If abstracts-cache.json is very large (>100 MB):
⚠️ abstracts-cache.json is 256 MB
This file enables re-screening if you update the rubric. Options:
1. Keep (recommended if you might refine rubric)
2. Compress (gzip to ~50 MB, can decompress later)
3. Delete (only if research is final and won't be updated)
Choice? (1/2/3)
📝 Found helper scripts:
- screen_papers.py (created for batch screening)
- deep_dive_papers.py (created for data extraction)
These scripts document your methodology. Recommendations:
- Keep for reproducibility
- Add comments if not already documented
- Reference in SUMMARY.md under "Reproducibility" section
Keep scripts? (y/n)
Case 3: Multiple Research Sessions
If cleaning up multiple sessions:
# Find all research sessions
find research-sessions/ -maxdepth 1 -type d
# For each session:
for session in research-sessions/*/; do
echo "Analyzing: $session"
# Run cleanup analysis
done
Ask user:
Found 5 completed research sessions.
Clean up all sessions? (y/n/select)
- y: Analyze and clean all sessions
- n: Cancel
- select: Choose which sessions to clean
Safety Mechanisms
Protected File List
Maintain hardcoded list of patterns to NEVER delete:
def is_protected(filepath):
"""Check if file matches any protected pattern"""
for pattern in PROTECTED_PATTERNS:
if fnmatch(filepath, pattern):
return True
return False
# Never delete protected files
if is_protected(file_to_delete):
print(f"⚠️ ERROR: {file_to_delete} is protected and cannot be deleted")
return
Dry Run Mode
Always show what will be deleted before doing it:
# Dry run (show only, don't delete)
echo "DRY RUN - No files will be deleted"
for file in $candidate_files; do
if is_safe_to_delete "$file"; then
echo "Would delete: $file ($(du -h $file | cut -f1))"
fi
done
echo ""
echo "Proceed with actual deletion? (y/n)"
Integration with Other Skills
After answering-research-questions workflow:
Complete Phase 8 (consolidation)
User reviews SUMMARY.md and relevant-papers.json
Optionally: Run cleaning-up-research-sessions
Archive or share research folder
Add to answering-research-questions Phase 8:
### Optional: Cleanup
After reviewing outputs, optionally clean up intermediate files:
"Research session is complete. Would you like me to clean up intermediate files?
I'll show you what will be deleted before removing anything."
If yes: Use `cleaning-up-research-sessions` skill
Common Mistakes
Deleting papers-reviewed.json: This is the deduplication database - NEVER delete → Always protect with hardcoded list
Deleting abstracts-cache.json: Needed for re-screening → Ask user, default to keep
Deleting helper scripts: Important for reproducibility → Keep by default, ask if user wants to remove
Not showing user what will be deleted: User needs to see the plan → Always show dry run first
Deleting without confirmation: Too risky → Always ask for final confirmation
Not verifying after cleanup: Files could be corrupted → Run integrity check after deletion
Quick Reference
Action
Command
List all files with sizes
find . -type f -exec ls -lh {} \; | sort -rh
Check if JSON valid
jq empty file.json
Move to trash (macOS)
mv file ~/.Trash/
Move to trash (Linux)
mv file ~/.local/share/Trash/files/
Compress large file
gzip file
Calculate folder size
du -sh .
Success Criteria
Cleanup successful when:
All protected files still exist and are valid
Only confirmed intermediate files deleted
User knows what was deleted and why
Space recovered is reported
Integrity check passed
Research session is still fully functional
Example Session
User: "Can you clean up the research session folder?"
Agent: "I'll analyze the research session and show you what can be safely cleaned up."
[Analyzes folder]
Agent: "🧹 Cleanup Analysis for: research-sessions/2025-10-11-btk-selectivity/
Files to KEEP (protected):
✅ SUMMARY.md (45 KB) - Final findings
✅ relevant-papers.json (12 KB) - Filtered results
✅ papers-reviewed.json (28 KB) - Complete history
✅ papers/ (14 PDFs, 32 MB) - Downloaded papers
✅ citations/citation-graph.json (5 KB) - Citation network
✅ screening-criteria.json (2 KB) - Rubric definition
✅ abstracts-cache.json (156 KB) - Cached abstracts
Files that CAN be removed:
🗑️ initial-search-results.json (8 KB) - Raw PubMed results
→ Data is preserved in papers-reviewed.json
🗑️ .DS_Store (6 KB) - macOS metadata
→ Not needed
Total space to recover: 14 KB
Proceed with cleanup? (y/n/review)"
User: "y"
Agent: "Final confirmation - About to delete:
- initial-search-results.json (8 KB)
- .DS_Store (6 KB)
All protected files will be preserved. Confirm? (y/n)"
User: "y"
Agent: [Deletes files]
"✅ Cleanup complete!
Removed:
- initial-search-results.json (8 KB)
- .DS_Store (6 KB)
Space recovered: 14 KB
Running integrity check...
✅ All core files intact
✅ All JSON files valid
✅ All 14 PDFs present
Research session is ready for archiving or sharing."
Next Steps
After cleanup:
Research folder is clean and ready to archive
Share folder with collaborators
Move to long-term storage
Continue with follow-up research if needed
How do I install Cleaning Up Research Sessions?
Download skills/05-kthorn-research-superpower/research/cleaning-up-research-sessions/SKILL.md from the publisher, or copy the path and open the repository. PlugMCP lists the skill and does not host the file.
Where does Cleaning Up Research Sessions live?
The publisher keeps it at https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.
Which agents can use Cleaning Up Research Sessions?
Claude, Cursor, and Codex can read a SKILL.md you add from the publisher's repository.