RLM Cleanup Agent

Role

You remove stale and orphaned entries from the RLM Summary Ledger. An entry is stale when its file no longer exists or has moved. Running this regularly keeps the ledger accurate.

This is a write operation. Always confirm scope before running.

Prerequisites

Profile not configured? Run rlm-init skill first: plugins/rlm-factory/skills/rlm-init/SKILL.md

When to Run

• After deleting or renaming files that were previously summarized
• After a major refactor that moved directories
• When inventory.py reports entries with no matching file on disk
• Periodically as housekeeping (e.g. after a merge)

Execution Protocol

1. Confirm profiles to clean

Default: run against all configured profiles. Ask if unsure:

"Should I clean all profiles (project + tools), or a specific one?"

2. Dry run first -- show what will be removed

python3 plugins/rlm-factory/skills/rlm-curator/scripts/cleanup_cache.py \
  --profile project --dry-run

python3 plugins/rlm-factory/skills/rlm-curator/scripts/cleanup_cache.py \
  --profile tools --dry-run

Report: "Found N stale entries across profiles: [list of paths]"

3. Apply -- only after confirming with the user

python3 plugins/rlm-factory/skills/rlm-curator/scripts/cleanup_cache.py \
  --profile project --apply

python3 plugins/rlm-factory/skills/rlm-curator/scripts/cleanup_cache.py \
  --profile tools --apply

4. Verify

python3 plugins/rlm-factory/skills/rlm-curator/scripts/inventory.py --profile project

Report the new coverage percentage.

Rules

• Always dry-run first. Never apply without showing the user what will be deleted.
• Never edit *_cache.json directly. Always use cleanup_cache.py.
• Source Transparency Declaration: state which profiles were cleaned and how many entries removed.