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qui_automations

Create, update, delete, apply, reorder, and validate qBittorrent automation rules, including dry runs and activity tracking, through direct API calls.

Instructions

qui automations operations on qui. Pass operation and an arguments object; path variables go directly in arguments, query values in arguments.params, and a JSON request body in arguments.body.

  • qui_apply_automations: POST /instances/{instanceID}/automations/apply

  • qui_create_automation: POST /instances/{instanceID}/automations/

  • qui_delete_automation: DELETE /instances/{instanceID}/automations/{ruleID}

  • qui_delete_automation_activity: DELETE /instances/{instanceID}/automations/activity

  • qui_dry_run_automations: POST /instances/{instanceID}/automations/dry-run

  • qui_get_automation_activity_run: GET /instances/{instanceID}/automations/activity/{activityId}

  • qui_list_automation_activity: GET /instances/{instanceID}/automations/activity

  • qui_list_automations: GET /instances/{instanceID}/automations/

  • qui_preview_automation_delete: POST /instances/{instanceID}/automations/preview

  • qui_reorder_automations: PUT /instances/{instanceID}/automations/order

  • qui_update_automation: PUT /instances/{instanceID}/automations/{ruleID}

  • qui_validate_automation_regex: POST /instances/{instanceID}/automations/validate-regex

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsNo
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It lists HTTP methods (GET, POST, PUT, DELETE) which imply mutating vs read-only behavior, and it includes a dry-run and preview operation. However, it doesn't disclose any side effects, permissions, rate limits, or what happens on deletion (e.g., whether it's reversible). The method hints are useful but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single paragraph with a clear instruction and a bulleted list of operations corrected with endpoints post-pended, which is efficient. However, it could be improved by summarizing the common pattern more concisely and perhaps grouping operations (e.g., list vs. mutate). The list of 12 operations is necessary for enumeration but adds length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no annotations and a low schema description coverage, the description must provide full context Sports. It gives the dispatch mechanism and lists all operations with endpoints, which is helpful. However, it lacks details on the actual arguments for each operation (e.g., required path parameters like instanceID and ruleID are not explicitly documented, though they appear in endpoints). It also doesn't describe return values, though an output schema exists (which helps). Overall, it's adequate but leaves gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has only two parameters: `operation` (an enum of all operations) and `arguments` (a free-form object). The description explains that `arguments` should contain path variables, query params, and body, but it doesn't detail what each operation expects within those arguments. Since schema coverage is 0%, the description must compensate, but it only lists endpoints without parameter specifics. For example, it doesn't explain what fields each automation operation requires, leaving significant ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that this tool handles automation operations, and it lists all 12 operations with their HTTP methods and endpoints, which identifies what it does. However, it does not explicitly distinguish from sibling tools beyond the domain of automations; siblings like qui_torrents and qui_instances are clearly different domains, so the purpose is distinct but not explicitly differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear usage pattern: pass `operation` and an `arguments` object, with detailed instructions on where path variables, query values, and JSON body go. It implicitly says when to use this tool (any automation-related operation) but doesn't explicitly state when-not-to-use or alternatives, as the sibling tools are for other domains.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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