drchronx/ai-agent-research-starter-kit/cleaning-up-research-sessions
Claude Code and agent skill by drchronx/ai-agent-research-starter-kit
- community
Checking that the SKILL.md file is still in the repository.
Safely remove intermediate files from completed research sessions while preserving important data
Install
npx vskill@latest install drchronx/ai-agent-research-starter-kit/cleaning-up-research-sessionsSKILL.md
The same SKILL.md was published earlier as kthorn/research-superpower/cleaning-up-research-sessions.
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 methodologyrelevant-papers.json- Filtered relevant paperspapers-reviewed.json- Complete screening historypapers/directory - All PDFs and supplementary filescitations/citation-graph.json- Citation relationships
Methodology documentation:
screening-criteria.json- Rubric definition (if exists)test-set.json- Rubric validation papers (if exists)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 overviewTOP_PRIORITY_PAPERS.md- Curated priority listevaluated-papers.json- Rich structured data
Project configuration:
.claude/directory - Permissions and settings*.pyhelper 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:
*.tmpfiles*.swpfiles (vim swap files).DS_Store(macOS)__pycache__/(Python cache)*.pyc(Python compiled)
Log files:
*.logfilesdebug-*.txtfiles
Cleanup Workflow
Step 1: Analyze Research Session
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:
Options:
y- Delete intermediate filesn- Cancel cleanup, keep everythingreview- 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:
Step 4: Perform Cleanup
Delete confirmed files:
Report results:
Step 5: Verify Integrity
After cleanup, verify critical files:
Report to user:
Special Cases
Case 1: Large abstracts-cache.json
If abstracts-cache.json is very large (>100 MB):
If user chooses compress:
Case 2: Helper Scripts
If user created helper scripts during research:
Case 3: Multiple Research Sessions
If cleaning up multiple sessions:
Ask user:
Safety Mechanisms
Protected File List
Maintain hardcoded list of patterns to NEVER delete:
Before deleting any file:
Dry Run Mode
Always show what will be deleted before doing it:
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:
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
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
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryChecking综合学术部署包/02_文献检索综述引用Skills/research-superpower/research/cleaning-up-research-sessions/SKILL.md
Popularity
- Repository stars
- 167
- Repository forks
- 12
- 7-day trend score
- 0
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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