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rlm-cleanup-agent

스타3

포크2

업데이트2026년 6월 7일 17:46

Removes stale and orphaned entries from the RLM Summary Ledger. Use after files are deleted, renamed, or moved to keep the ledger in sync with the filesystem. <example> user: "Clean up the RLM cache after I renamed some files" assistant: "I'll use rlm-cleanup-agent to remove stale entries from the ledger." </example> <example> user: "The RLM ledger has entries for files that no longer exist" assistant: "I'll run rlm-cleanup-agent to prune orphaned entries." </example>

설치

Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.

Manus에서 실행

출처

richfrem

richfrem/agent-plugins-skills

GitHub 저장소 열기 Creator 저장소 보기

다운로드

Manus에서 실행

Dependencies

This skill requires Python 3.8+ and standard library only. No external packages needed.

To install this skill's dependencies:

pip-compile ./requirements.in
pip install -r ./requirements.txt

See ./requirements.txt for the dependency lockfile (currently empty — standard library only).

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: 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

python ./scripts/cleanup_cache.py \
  --profile project --dry-run

python ./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

python ./scripts/cleanup_cache.py \
  --profile project --apply

python ./scripts/cleanup_cache.py \
  --profile tools --apply

4. Verify

python ./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/*.md directly. Always use cleanup_cache.py.
Source Transparency Declaration: state which profiles were cleaned and how many entries removed.

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name	rlm-cleanup-agent
plugin	rlm-factory
description	Removes stale and orphaned entries from the RLM Summary Ledger. Use after files are deleted, renamed, or moved to keep the ledger in sync with the filesystem. <example> user: "Clean up the RLM cache after I renamed some files" assistant: "I'll use rlm-cleanup-agent to remove stale entries from the ledger." </example> <example> user: "The RLM ledger has entries for files that no longer exist" assistant: "I'll run rlm-cleanup-agent to prune orphaned entries." </example>
allowed-tools	Bash, Read, Write

Dependencies

This skill requires Python 3.8+ and standard library only. No external packages needed.

To install this skill's dependencies:

pip-compile ./requirements.in
pip install -r ./requirements.txt

See ./requirements.txt for the dependency lockfile (currently empty — standard library only).

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: 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

python ./scripts/cleanup_cache.py \
  --profile project --dry-run

python ./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

python ./scripts/cleanup_cache.py \
  --profile project --apply

python ./scripts/cleanup_cache.py \
  --profile tools --apply

4. Verify

python ./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/*.md directly. Always use cleanup_cache.py.
Source Transparency Declaration: state which profiles were cleaned and how many entries removed.