How do I install the Qbittorrent Completed Cleaner skill?

Run npx skillmds@latest add knuckles-team/qbittorrent-completed-cleaner in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Qbittorrent Completed Cleaner safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Qbittorrent Completed Cleaner?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Qbittorrent Completed Cleaner free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Qbittorrent Completed Cleaner?

Knuckles-Team (@knuckles-team) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Qbittorrent Completed Cleaner by knuckles-team

Name: Qbittorrent Completed Cleaner
Author: Knuckles-Team

File contents

Qbittorrent Completed Cleaner Workflow

CONCEPT:INFRA-001

Discovers completed downloads, prompts the user to select torrents to remove, and securely prunes the active dashboard list (optionally deleting files).

Steps

Step 0: list-completed-torrents [skill: qbittorrent-agent]

Agent: discovery-agent Tools: tun_tm_system, tun_tm_hosts

Fetch all completed torrents that are currently seeding or finished downloading using qbittorrent_torrents with the get_torrent_list action. Expected: completed_torrent_list

Step 1: User Interaction

Agent: deployer-agent Tools: pt_stack, cnt_cm_compose_operations

Display completed torrents. Prompt the user to select which completed items should be deleted, and confirm if actual data files should also be erased. Expected: selected_hashes, delete_files_flag

Step 2: delete-selected-torrents [skill: qbittorrent-agent]

Agent: verifier-agent Tools: pt_docker, cnt_cm_container_operations

Remove the chosen torrents using qbittorrent_torrents with the delete_torrents action, passing the target hashes and deletion options. Expected: pruning_results

Step 3: KG Persistence [depends_on: Step 0, Step 2]

Agent: verifier-agent Tools: graph_write

Persist workflow results as nodes and edges in the Knowledge Graph. Create appropriate typed nodes with metadata and link to existing domain entities.

Output

Qbittorrent Completed Cleaner results persisted in KG
Structured report (MD/PDF)
Audit trail with timestamps and agent attributions

Execution

Run this workflow as a dependency-ordered DAG. Steps with no unmet depends_on run in parallel; dependents run after their prerequisites complete.

Run first (in parallel): Step 0 — list-completed-torrents; Step 1 — User Interaction; Step 2 — delete-selected-torrents
After level 0: Step 3 — KG Persistence

Execution: If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.

---name: qbittorrent-completed-cleanerdescription: Discovers completed downloads, prompts the user to select torrents to remove, and securely prunes the active dashboard list (optionally deleting files).---# Qbittorrent Completed Cleaner Workflow**CONCEPT:INFRA-001**Discovers completed downloads, prompts the user to select torrents to remove, and securely prunes the active dashboard list (optionally deleting files).## Steps### Step 0: list-completed-torrents [skill: qbittorrent-agent]**Agent**: `discovery-agent`**Tools**: `tun_tm_system, tun_tm_hosts`Fetch all completed torrents that are currently seeding or finished downloading using qbittorrent_torrents with the get_torrent_list action.Expected: `completed_torrent_list`### Step 1: User Interaction**Agent**: `deployer-agent`**Tools**: `pt_stack, cnt_cm_compose_operations`Display completed torrents. Prompt the user to select which completed items should be deleted, and confirm if actual data files should also be erased.Expected: `selected_hashes, delete_files_flag`### Step 2: delete-selected-torrents [skill: qbittorrent-agent]**Agent**: `verifier-agent`**Tools**: `pt_docker, cnt_cm_container_operations`Remove the chosen torrents using qbittorrent_torrents with the delete_torrents action, passing the target hashes and deletion options.Expected: `pruning_results`### Step 3: KG Persistence [depends_on: Step 0, Step 2]**Agent**: `verifier-agent`**Tools**: `graph_write`Persist workflow results as nodes and edges in the Knowledge Graph.Create appropriate typed nodes with metadata and link to existing domain entities.## Output- Qbittorrent Completed Cleaner results persisted in KG- Structured report (MD/PDF)- Audit trail with timestamps and agent attributions## ExecutionRun this workflow as a dependency-ordered DAG. Steps with no unmet `depends_on` run in parallel; dependents run after their prerequisites complete.- **Run first (in parallel):** Step 0 — list-completed-torrents; Step 1 — User Interaction; Step 2 — delete-selected-torrents- **After level 0:** Step 3 — KG Persistence**Execution:** If graph-os is reachable, offload the whole DAG via `graph_orchestrate action=execute_workflow` (or the `kg-delegate` skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet `depends_on` in parallel, then their dependents.

Frequently asked questions

Qbittorrent Completed Cleaner