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SavageCore

autobrr-mcp

by SavageCore

autobrr_release

Perform release operations on autobrr: list, retrieve, delete, and analyze releases, and manage cleanup jobs and duplicate profiles.

Instructions

autobrr release operations on autobrr. Pass operation and an arguments dict matching that operation's parameters.

  • autobrr_create_cleanup_job(body={}) — Create a release cleanup job. WRITE: this modifies your autobrr instance.

  • autobrr_create_duplicate_profile(body={}) — Create a duplicate release profile. WRITE: this modifies your autobrr instance.

  • autobrr_delete_cleanup_job(job_id) — Delete a cleanup job. DESTRUCTIVE: this deletes data.

  • autobrr_delete_duplicate_profile(profile_id) — Delete a duplicate release profile. DESTRUCTIVE: this deletes data.

  • autobrr_delete_releases(older_than=0, indexer=None, release_status=None) — Delete releases. Query params: olderThan, indexer (repeatable), releaseStatus (repeatable: PUSH_APPROVED|PUSH_REJECTED|PUSH_ERROR|PENDING). DESTRUCTIVE: this deletes data.

  • autobrr_get_cleanup_job(job_id) — Fetch a single cleanup job by id.

  • autobrr_get_release(release_id) — Fetch a single release by id.

  • autobrr_get_release_stats() — Overall release stats (total, approved, rejected, etc.).

  • autobrr_get_release_stats_activity(days=30) — Release activity stats. Query params: days (default 30).

  • autobrr_get_release_stats_heatmap(days=30) — Release heatmap stats. Query params: days (default 30).

  • autobrr_get_release_stats_top_filters(days=30) — Top filters by release count. Query params: days (default 30).

  • autobrr_get_release_stats_top_indexers(days=30) — Top indexers by release count. Query params: days (default 30).

  • autobrr_get_release_stats_volume(days=30) — Release volume stats. Query params: days (default 30).

  • autobrr_list_cleanup_jobs() — List release cleanup jobs.

  • autobrr_list_duplicate_profiles() — List duplicate release profiles.

  • autobrr_list_recent_releases() — List the 10 most recent releases.

  • autobrr_list_release_indexer_options() — List the indexer names available as release filters.

  • autobrr_list_releases(limit=20, offset=0, cursor=0, indexer=None, push_status='', q='') — List releases (the IRC/feed queue). Query params: limit, offset, cursor, indexer (repeatable), push_status (PUSH_APPROVED|PUSH_REJECTED|PUSH_ERROR|PENDING), q.

  • autobrr_retry_release_action(release_id, action_status_id) — Retry a failed action for a release. WRITE: this modifies your autobrr instance.

  • autobrr_run_cleanup_job(job_id) — Force a cleanup job to run now. WRITE: this modifies your autobrr instance.

  • autobrr_toggle_cleanup_job_enabled(job_id, body={}) — Enable or disable a cleanup job (body: {"enabled": bool}). WRITE: this modifies your autobrr instance.

  • autobrr_update_cleanup_job(job_id, body={}) — Update a cleanup job. WRITE: this modifies your autobrr instance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsNo
operationYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It explicitly labels write operations as 'WRITE: this modifies your autobrr instance' and destructive ones as 'DESTRUCTIVE: this deletes data', which is meaningful and safety-relevant. It does not cover auth, rate limits, or reversibility, but the mutation/destruction flags add real transparency beyond the bare operation names.

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

Conciseness4/5

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

The description is long but necessarily so for 22 operations. It is structured as a clear bulleted list with each operation on one concise line, and the repeated WRITE/DESTRUCTIVE tags provide consistent safety cues without bloating each line. The length is justified by the number of sub-operations, and the list format makes it easy to scan.

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

Completeness4/5

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

Given the complexity of a 22-operation dispatcher, the description covers each operation's purpose and key parameters, and an output schema exists to handle return values. The main gaps are that `arguments` construction for body-bearing operations lacks field-level detail and there are no explicit error or authentication notes, but overall it is reasonably complete for its scope.

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

Parameters4/5

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

The input schema only exposes `operation` and an opaque `arguments` object, so the description is the only source of parameter meaning. It includes parameter names, defaults, and enum values for many sub-operations (e.g., older_than=0, days=30, push_status=PUSH_APPROVED|...), which is critical for constructing valid arguments. However, body dicts are only hinted via `body={}` without detailed field definitions.

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 identifies this as a dispatcher for autobrr release operations and enumerates 22 concrete sub-operations with one-line explanations, making the tool's scope specific. The release domain distinguishes it from sibling tools like autobrr_filters and autobrr_actions, though it does not explicitly contrast them.

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

Usage Guidelines3/5

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

The description gives the invocation pattern ('Pass operation and an arguments dict') and lists the available operations, so it is easy to understand how to use the tool. However, it never explicitly states when to choose this tool over sibling tools or provides exclusions, leaving usage timing to be inferred from the name and operation list.

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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